{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluating the Results\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quick look at the data\n",
    "\n",
    "Just as a quick reference to remember which columns are available.\n",
    "Double check for stupid mistakes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instance_name</th>\n",
       "      <th>num_nodes</th>\n",
       "      <th>time_limit</th>\n",
       "      <th>strategy</th>\n",
       "      <th>opt_tol</th>\n",
       "      <th>runtime</th>\n",
       "      <th>objective</th>\n",
       "      <th>lower_bound</th>\n",
       "      <th>opt_gap</th>\n",
       "      <th>opt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>random_euclidean_25_0</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>Dantzig (Gurobi)</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.048017</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>96367438.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>random_euclidean_25_0</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>Dantzig (Gurobi)</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.046579</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>96367438.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>random_euclidean_25_0</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>Dantzig (Gurobi)</td>\n",
       "      <td>0.050</td>\n",
       "      <td>0.024580</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>96367438.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>random_euclidean_25_0</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>Dantzig (Gurobi)</td>\n",
       "      <td>0.100</td>\n",
       "      <td>0.015548</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>96367438.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>random_euclidean_25_0</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>Dantzig (Gurobi)</td>\n",
       "      <td>0.250</td>\n",
       "      <td>0.007838</td>\n",
       "      <td>1.216670e+08</td>\n",
       "      <td>94403263.0</td>\n",
       "      <td>0.224085</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>358</th>\n",
       "      <td>random_euclidean_500_9</td>\n",
       "      <td>500</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.001</td>\n",
       "      <td>100.248195</td>\n",
       "      <td>9.412218e+09</td>\n",
       "      <td>66738473.0</td>\n",
       "      <td>0.992909</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>359</th>\n",
       "      <td>random_euclidean_500_9</td>\n",
       "      <td>500</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.010</td>\n",
       "      <td>104.222358</td>\n",
       "      <td>1.151326e+10</td>\n",
       "      <td>66738473.0</td>\n",
       "      <td>0.994203</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>random_euclidean_500_9</td>\n",
       "      <td>500</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.050</td>\n",
       "      <td>99.913106</td>\n",
       "      <td>7.924827e+09</td>\n",
       "      <td>66738473.0</td>\n",
       "      <td>0.991579</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>random_euclidean_500_9</td>\n",
       "      <td>500</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.100</td>\n",
       "      <td>200.734578</td>\n",
       "      <td>9.848627e+09</td>\n",
       "      <td>66738473.0</td>\n",
       "      <td>0.993224</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>random_euclidean_500_9</td>\n",
       "      <td>500</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.250</td>\n",
       "      <td>100.519814</td>\n",
       "      <td>9.293126e+09</td>\n",
       "      <td>66738473.0</td>\n",
       "      <td>0.992819</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2400 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               instance_name  num_nodes  time_limit              strategy  \\\n",
       "1985   random_euclidean_25_0         25          90      Dantzig (Gurobi)   \n",
       "1986   random_euclidean_25_0         25          90      Dantzig (Gurobi)   \n",
       "1987   random_euclidean_25_0         25          90      Dantzig (Gurobi)   \n",
       "1988   random_euclidean_25_0         25          90      Dantzig (Gurobi)   \n",
       "1989   random_euclidean_25_0         25          90      Dantzig (Gurobi)   \n",
       "...                      ...        ...         ...                   ...   \n",
       "358   random_euclidean_500_9        500          90  Miller-Tucker-Zemlin   \n",
       "359   random_euclidean_500_9        500          90  Miller-Tucker-Zemlin   \n",
       "360   random_euclidean_500_9        500          90  Miller-Tucker-Zemlin   \n",
       "361   random_euclidean_500_9        500          90  Miller-Tucker-Zemlin   \n",
       "362   random_euclidean_500_9        500          90  Miller-Tucker-Zemlin   \n",
       "\n",
       "      opt_tol     runtime     objective  lower_bound   opt_gap    opt  \n",
       "1985    0.001    0.048017  9.636744e+07   96367438.0  0.000000   True  \n",
       "1986    0.010    0.046579  9.636744e+07   96367438.0  0.000000   True  \n",
       "1987    0.050    0.024580  9.636744e+07   96367438.0  0.000000   True  \n",
       "1988    0.100    0.015548  9.636744e+07   96367438.0  0.000000   True  \n",
       "1989    0.250    0.007838  1.216670e+08   94403263.0  0.224085  False  \n",
       "...       ...         ...           ...          ...       ...    ...  \n",
       "358     0.001  100.248195  9.412218e+09   66738473.0  0.992909  False  \n",
       "359     0.010  104.222358  1.151326e+10   66738473.0  0.994203  False  \n",
       "360     0.050   99.913106  7.924827e+09   66738473.0  0.991579  False  \n",
       "361     0.100  200.734578  9.848627e+09   66738473.0  0.993224  False  \n",
       "362     0.250  100.519814  9.293126e+09   66738473.0  0.992819  False  \n",
       "\n",
       "[2400 rows x 10 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from _conf import SIMPLIFIED_RESULTS, PUBLIC_DATA\n",
    "\n",
    "results = pd.read_json(SIMPLIFIED_RESULTS)\n",
    "results[\"opt_gap\"] = (results[\"objective\"] - results[\"lower_bound\"]) / results[\n",
    "    \"objective\"\n",
    "]\n",
    "results[\"strategy\"].replace(\n",
    "    {\n",
    "        \"GurobiTspSolver\": \"Dantzig (Gurobi)\",\n",
    "        \"CpSatTspSolverV1\": \"AddCircuit\",\n",
    "        \"CpSatTspSolverDantzig\": \"Iterative Dantzig\",\n",
    "        \"CpSatTspSolverMtz\": \"Miller-Tucker-Zemlin\",\n",
    "    },\n",
    "    inplace=True,\n",
    ")\n",
    "results[\"opt\"] = results[\"opt_gap\"] <= 0.001\n",
    "results.sort_values([\"num_nodes\", \"instance_name\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>instance_name</th>\n",
       "      <th>num_nodes</th>\n",
       "      <th>time_limit</th>\n",
       "      <th>strategy</th>\n",
       "      <th>opt_tol</th>\n",
       "      <th>runtime</th>\n",
       "      <th>objective</th>\n",
       "      <th>lower_bound</th>\n",
       "      <th>opt_gap</th>\n",
       "      <th>opt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>random_euclidean_25_0</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>Dantzig (Gurobi)</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.048017</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>random_euclidean_25_0</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>AddCircuit</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.243726</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>random_euclidean_25_0</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>Iterative Dantzig</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.222666</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>random_euclidean_25_0</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.644817</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>9.636744e+07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>random_euclidean_25_1</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>Dantzig (Gurobi)</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.024823</td>\n",
       "      <td>9.077355e+07</td>\n",
       "      <td>9.077355e+07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338</th>\n",
       "      <td>random_euclidean_500_8</td>\n",
       "      <td>500</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.001</td>\n",
       "      <td>100.883436</td>\n",
       "      <td>8.984455e+09</td>\n",
       "      <td>6.272751e+07</td>\n",
       "      <td>0.993018</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343</th>\n",
       "      <td>random_euclidean_500_9</td>\n",
       "      <td>500</td>\n",
       "      <td>90</td>\n",
       "      <td>Dantzig (Gurobi)</td>\n",
       "      <td>0.001</td>\n",
       "      <td>70.489049</td>\n",
       "      <td>7.378162e+07</td>\n",
       "      <td>7.371034e+07</td>\n",
       "      <td>0.000966</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>348</th>\n",
       "      <td>random_euclidean_500_9</td>\n",
       "      <td>500</td>\n",
       "      <td>90</td>\n",
       "      <td>AddCircuit</td>\n",
       "      <td>0.001</td>\n",
       "      <td>95.834668</td>\n",
       "      <td>3.011006e+08</td>\n",
       "      <td>6.539077e+07</td>\n",
       "      <td>0.782828</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>353</th>\n",
       "      <td>random_euclidean_500_9</td>\n",
       "      <td>500</td>\n",
       "      <td>90</td>\n",
       "      <td>Iterative Dantzig</td>\n",
       "      <td>0.001</td>\n",
       "      <td>108.669239</td>\n",
       "      <td>1.596116e+10</td>\n",
       "      <td>7.176012e+07</td>\n",
       "      <td>0.995504</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>358</th>\n",
       "      <td>random_euclidean_500_9</td>\n",
       "      <td>500</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.001</td>\n",
       "      <td>100.248195</td>\n",
       "      <td>9.412218e+09</td>\n",
       "      <td>6.673847e+07</td>\n",
       "      <td>0.992909</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>480 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               instance_name  num_nodes  time_limit              strategy  \\\n",
       "1985   random_euclidean_25_0         25          90      Dantzig (Gurobi)   \n",
       "1990   random_euclidean_25_0         25          90            AddCircuit   \n",
       "1995   random_euclidean_25_0         25          90     Iterative Dantzig   \n",
       "2000   random_euclidean_25_0         25          90  Miller-Tucker-Zemlin   \n",
       "2005   random_euclidean_25_1         25          90      Dantzig (Gurobi)   \n",
       "...                      ...        ...         ...                   ...   \n",
       "338   random_euclidean_500_8        500          90  Miller-Tucker-Zemlin   \n",
       "343   random_euclidean_500_9        500          90      Dantzig (Gurobi)   \n",
       "348   random_euclidean_500_9        500          90            AddCircuit   \n",
       "353   random_euclidean_500_9        500          90     Iterative Dantzig   \n",
       "358   random_euclidean_500_9        500          90  Miller-Tucker-Zemlin   \n",
       "\n",
       "      opt_tol     runtime     objective   lower_bound   opt_gap    opt  \n",
       "1985    0.001    0.048017  9.636744e+07  9.636744e+07  0.000000   True  \n",
       "1990    0.001    0.243726  9.636744e+07  9.636744e+07  0.000000   True  \n",
       "1995    0.001    0.222666  9.636744e+07  9.636744e+07  0.000000   True  \n",
       "2000    0.001    0.644817  9.636744e+07  9.636744e+07  0.000000   True  \n",
       "2005    0.001    0.024823  9.077355e+07  9.077355e+07  0.000000   True  \n",
       "...       ...         ...           ...           ...       ...    ...  \n",
       "338     0.001  100.883436  8.984455e+09  6.272751e+07  0.993018  False  \n",
       "343     0.001   70.489049  7.378162e+07  7.371034e+07  0.000966   True  \n",
       "348     0.001   95.834668  3.011006e+08  6.539077e+07  0.782828  False  \n",
       "353     0.001  108.669239  1.596116e+10  7.176012e+07  0.995504  False  \n",
       "358     0.001  100.248195  9.412218e+09  6.673847e+07  0.992909  False  \n",
       "\n",
       "[480 rows x 10 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = results.sort_values([\"num_nodes\", \"instance_name\"])\n",
    "t[t[\"opt_tol\"] == 0.001]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sns.set_theme()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Looking at the runtime\n",
    "\n",
    "We can take a quick look at the runtime of the different models.\n",
    "This is a good sanity check to see if the models are actually running.\n",
    "However, you will notice the sigmoidal shape of the runtime.\n",
    "The instances do not suddenly get easier, but the runtime is limited by the timeout.\n",
    "The true runtime can be expected to be an exponential curve.\n",
    "For this reason, this is not a good metric to compare the models and may be misleading."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>runtime</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>num_nodes</th>\n",
       "      <th>strategy</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">25</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>0.073352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>0.032130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>0.248574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>0.409975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">50</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>0.442609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>0.114854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>24.349491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>10.097673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">75</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>1.952957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>0.220298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>76.774528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>68.858994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">100</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>8.060139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>0.470333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>82.334937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>86.986115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">150</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>30.369175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>1.140127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>91.048224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>91.513630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">200</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>77.763684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>2.732445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>91.698779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>94.195183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">250</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>91.700525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>8.670386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>91.921212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>101.799496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">300</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>92.403233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>11.126396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>103.828611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>120.046600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">350</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>93.068392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>24.867971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>122.044434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>132.205184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">400</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>93.853760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>49.211782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>115.309117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>191.991516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">450</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>94.895319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>60.149384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>126.163162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>408.444933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">500</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>95.791659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>66.626697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>126.472907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>101.228467</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   runtime\n",
       "num_nodes strategy                        \n",
       "25        AddCircuit              0.073352\n",
       "          Dantzig (Gurobi)        0.032130\n",
       "          Iterative Dantzig       0.248574\n",
       "          Miller-Tucker-Zemlin    0.409975\n",
       "50        AddCircuit              0.442609\n",
       "          Dantzig (Gurobi)        0.114854\n",
       "          Iterative Dantzig      24.349491\n",
       "          Miller-Tucker-Zemlin   10.097673\n",
       "75        AddCircuit              1.952957\n",
       "          Dantzig (Gurobi)        0.220298\n",
       "          Iterative Dantzig      76.774528\n",
       "          Miller-Tucker-Zemlin   68.858994\n",
       "100       AddCircuit              8.060139\n",
       "          Dantzig (Gurobi)        0.470333\n",
       "          Iterative Dantzig      82.334937\n",
       "          Miller-Tucker-Zemlin   86.986115\n",
       "150       AddCircuit             30.369175\n",
       "          Dantzig (Gurobi)        1.140127\n",
       "          Iterative Dantzig      91.048224\n",
       "          Miller-Tucker-Zemlin   91.513630\n",
       "200       AddCircuit             77.763684\n",
       "          Dantzig (Gurobi)        2.732445\n",
       "          Iterative Dantzig      91.698779\n",
       "          Miller-Tucker-Zemlin   94.195183\n",
       "250       AddCircuit             91.700525\n",
       "          Dantzig (Gurobi)        8.670386\n",
       "          Iterative Dantzig      91.921212\n",
       "          Miller-Tucker-Zemlin  101.799496\n",
       "300       AddCircuit             92.403233\n",
       "          Dantzig (Gurobi)       11.126396\n",
       "          Iterative Dantzig     103.828611\n",
       "          Miller-Tucker-Zemlin  120.046600\n",
       "350       AddCircuit             93.068392\n",
       "          Dantzig (Gurobi)       24.867971\n",
       "          Iterative Dantzig     122.044434\n",
       "          Miller-Tucker-Zemlin  132.205184\n",
       "400       AddCircuit             93.853760\n",
       "          Dantzig (Gurobi)       49.211782\n",
       "          Iterative Dantzig     115.309117\n",
       "          Miller-Tucker-Zemlin  191.991516\n",
       "450       AddCircuit             94.895319\n",
       "          Dantzig (Gurobi)       60.149384\n",
       "          Iterative Dantzig     126.163162\n",
       "          Miller-Tucker-Zemlin  408.444933\n",
       "500       AddCircuit             95.791659\n",
       "          Dantzig (Gurobi)       66.626697\n",
       "          Iterative Dantzig     126.472907\n",
       "          Miller-Tucker-Zemlin  101.228467"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display\n",
    "\n",
    "t = results.sort_values([\"num_nodes\", \"instance_name\"])\n",
    "t = t[t[\"opt_tol\"] == 0.001]\n",
    "display(t.groupby([\"num_nodes\", \"strategy\"])[[\"runtime\"]].mean())\n",
    "plt.figure(figsize=(7, 3.5))\n",
    "sns.lineplot(data=t.sort_values(\"strategy\"), x=\"num_nodes\", y=\"runtime\", hue=\"strategy\")\n",
    "plt.ylabel(\"Runtime (s)\")\n",
    "plt.title(\"Lower is better\")\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.xlabel(\"Number of nodes\")\n",
    "plt.ylim(-5, 120)\n",
    "plt.tight_layout()\n",
    "plt.savefig(PUBLIC_DATA / \"runtime.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting how many instances could still be solved to optimality\n",
    "\n",
    "This is a more interesting metric.\n",
    "Suddenly, we also see some differences between the `CpSatTspSolverMtz` and `CpSatTspSolverDantzig` models.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>opt_perc</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>num_nodes</th>\n",
       "      <th>strategy</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">25</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">50</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">75</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">100</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">150</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">200</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">250</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">300</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">350</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">400</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">450</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">500</th>\n",
       "      <th>AddCircuit</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dantzig (Gurobi)</th>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iterative Dantzig</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miller-Tucker-Zemlin</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                opt_perc\n",
       "num_nodes strategy                      \n",
       "25        AddCircuit               100.0\n",
       "          Dantzig (Gurobi)         100.0\n",
       "          Iterative Dantzig        100.0\n",
       "          Miller-Tucker-Zemlin     100.0\n",
       "50        AddCircuit               100.0\n",
       "          Dantzig (Gurobi)         100.0\n",
       "          Iterative Dantzig         90.0\n",
       "          Miller-Tucker-Zemlin     100.0\n",
       "75        AddCircuit               100.0\n",
       "          Dantzig (Gurobi)         100.0\n",
       "          Iterative Dantzig         70.0\n",
       "          Miller-Tucker-Zemlin      40.0\n",
       "100       AddCircuit               100.0\n",
       "          Dantzig (Gurobi)         100.0\n",
       "          Iterative Dantzig        100.0\n",
       "          Miller-Tucker-Zemlin      10.0\n",
       "150       AddCircuit               100.0\n",
       "          Dantzig (Gurobi)         100.0\n",
       "          Iterative Dantzig         20.0\n",
       "          Miller-Tucker-Zemlin       0.0\n",
       "200       AddCircuit                50.0\n",
       "          Dantzig (Gurobi)         100.0\n",
       "          Iterative Dantzig          0.0\n",
       "          Miller-Tucker-Zemlin       0.0\n",
       "250       AddCircuit                 0.0\n",
       "          Dantzig (Gurobi)         100.0\n",
       "          Iterative Dantzig          0.0\n",
       "          Miller-Tucker-Zemlin       0.0\n",
       "300       AddCircuit                 0.0\n",
       "          Dantzig (Gurobi)         100.0\n",
       "          Iterative Dantzig          0.0\n",
       "          Miller-Tucker-Zemlin       0.0\n",
       "350       AddCircuit                 0.0\n",
       "          Dantzig (Gurobi)         100.0\n",
       "          Iterative Dantzig          0.0\n",
       "          Miller-Tucker-Zemlin       0.0\n",
       "400       AddCircuit                 0.0\n",
       "          Dantzig (Gurobi)          80.0\n",
       "          Iterative Dantzig          0.0\n",
       "          Miller-Tucker-Zemlin       0.0\n",
       "450       AddCircuit                 0.0\n",
       "          Dantzig (Gurobi)          70.0\n",
       "          Iterative Dantzig          0.0\n",
       "          Miller-Tucker-Zemlin       0.0\n",
       "500       AddCircuit                 0.0\n",
       "          Dantzig (Gurobi)          80.0\n",
       "          Iterative Dantzig          0.0\n",
       "          Miller-Tucker-Zemlin       0.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = results.sort_values([\"num_nodes\", \"instance_name\"])\n",
    "t = t[t[\"opt_tol\"] == 0.001]\n",
    "t[\"opt_perc\"] = t[\"opt\"] * 100\n",
    "display(t.groupby([\"num_nodes\", \"strategy\"])[[\"opt_perc\"]].mean())\n",
    "plt.figure(figsize=(7, 3.5))\n",
    "t.rename(columns={\"strategy\": \"Strategy\"}, inplace=True)\n",
    "sns.lineplot(\n",
    "    data=t.sort_values(\"Strategy\"), x=\"num_nodes\", y=\"opt_perc\", hue=\"Strategy\"\n",
    ")\n",
    "plt.ylabel(\"Instances solved to optimality (%)\")\n",
    "plt.xlabel(\"Number of nodes\")\n",
    "plt.title(\"Higher is better\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(PUBLIC_DATA / \"solved_over_size.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, getting nearly optimal solutions is often signficantly easier than getting optimal solutions.\n",
    "For this reason, we may also want to check if the performance changes when we relax the optimality tolerance.\n",
    "Often, the data is inaccurate anyway, such that a 5% or even 20% optimality gap can be acceptable.\n",
    "We actually see that the `CpSatTspSolvingMtz` is better than `CpSatTspSolvingDantzig` for a 20% optimality gap.\n",
    "Also the `CpSatTspSolvingV1` model can solve significantly larger models if we relax the optimality tolerance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sFlC6OP5arWA1gygHuRysFrCYQBBBqQabDcxGkMlR1esMgPHEZrDbQJCBKHO8z/5s3vxXULmQLldiNWSB1QRyFYgimE2ObVGOoNIiKNTYMpNuOh/HuNjB3Q9RrsSWGgc2C2g9kLn6YDfqHefkjG23Z8skOGRHAEFA0Hogc/XGmpGEPSsFVfNH0Lbud+cvcQWQc48pzb3mXqWy58ZmszqVVVdX90qRoSAEwTEnVquNyl0rrXpIc3N7KmpulErH71xmZgpeXt6IoqyQM+5MlVdY09IcSoK7e96bRM52zvH09HSUSiVqtTpPOw8PDwBSU1NLpbC6u2tKfO7uVfPwSLfm7rj1A2K9Zdtov+NxYwo4tNdczDe9V7ja8Q9KxmKFhHiHDhEYmgxATHxOK1u+83IFs+OuzsTFHTJ0kBkPWrsdN18jehNkxTva1Ig3AaDzAbdQG/5icq4yDrgIeXv3FPR4GqLztAFAKHhZQibY8Mchd47SriIrj7xywZRnW8HN2yCz6rElXXN+0EWsyG1W0BsKHBPsyG75B8mMqShu3pERgw1u2pdXfhlmlMb4PPswZAFZzmcTDJabLsuKzJb3nyyz590WTRnYkjJyx7TosKXrboqatCOz3XpNVlwsabkimm85bDY6Xjno0/Iet1nBctNxuzX7OnJkMGE8tinvOXaLQ4m8DXZdWt6P862+gFYzdl0adm6R5WbS4vPOeFYq1qzU27e327n5f2RPT8CSnuDcNh5YiVfD1mir1bl9HxVIae419zqVNTcGgwFRFNFq1cjlVe+BQnrIuT3S3NyeipgbrVaNTifi4pJfPysuVV5hzeF2yy837y+oTY6LbmmXb9LT9VitJfP3CO34AIf37qB6nAW74Jh0Acg26OX+F7J/V+1qGYLdDiYb2WZQBzcpHIogGTZBlm1JE5DjsMwJ2LEpZFwXA5DJdWiCUxEEgetiEACa4FhEbJizpZBhQczuI/cF6a5upIpatC4JaILNCFqRVLsGu8qCKtjMTk8VWoOdehcM6JNAnwq2Gh5ovc24CnoAslADIlq7AUGwkSa4keEajibzKh72NKfdzYoMGVbs9mxjGHZkOKy2SXJ/sNlwtaejsFvIEl1Q2E24oMOGiAEVdgQ06LEjYkIBggw1RkSsWBWuaH0DMaYkgiEVGzKscg0yrTtWXTo2O9itVhSYnFZqa/aEizmfGa0XWVY5KkMSAnaU3sEoVAr0sZcR7WZsOKzdAnZEbFgEJUaXAGwmI2pDEqJgQ651R6ZQYc5IBkFAqXVxjJWZilWQYxVV2AUBmc2EYLdhE+SIdgtitrXQrvVG5eGFIS0Z9Omg0KBy98SSlojdrMcuiJhlWgS7HblV7/gcCHKyZO7YjFkoFTJctQqHvVKf4bA8KjUIciV2ixmsZgSNO9gsjm2LEWQKBIUKu9kEZj2IMgS1K3arBYw6BIUKVaP7ATAcXu9QcGUKh2XWbsu1btrtDgun3Yao9UCmVGLOSgezEUGpBVHEbjI4xpArEdRuCCotttRY8lhYrdlfAK/qyJRKrElXwWJCcPND5uGH3ZCFNT3eIYfd7rDI2q2OsUWZ09Iqungjc/fFkhaPPeU6APGrPkfd9TksFw/i0nFwib7npUUmE3F315TqXnOvUtlzYzIZs4OtqFL+xZIV8fZIc3N7KnJurFZHrFJamg69/lbrnOMh9K7xYS2MHAtpjiU1h/T0dCDX0uru7o7RaMRoNKJSqfK1y+mnpFitthLfqAK8grENe4LZl/4GQBREPu80Hbm8eNMfM+9HMnbtAMD/f6/h0rBRieQpLWazmZ3bJwFwtLaG/odBFZ+CeCENQVEX1yHPogwMxPuW827dLgp+RWy39fB1fvrrNDUC3Xi0cy1C/Fzxcsv9HGhLMPbNFCT77frMCRDZsv8yH68+TpbBgo9VzQcj2uJWyifa4l5HSea8JCia9y9Su6oQPHMz+kN/Ytm/HFtaHLo/PgS7DdOZXbj0exvRvaifvrKlNPeae53Kmpuq6geZo2xICll+pLm5PZUxN1arvdTf3SpvKw8NDUWhUHDhwoU8+8+dOwc4fFRv/pvjy5rD+fPncXFxISAgoAKkvT29anWnnrcjtZbNbmP8rneL3Ydrs+YACCo1quqhZSpfcVh6drXzfZyvgqgnWuA74HEEpRL96WguT5uM7tTJCpWpWR2HcnE5NoPPlx3hm9XHsFSylapJbV/eH96WtvUDeLJHHeTZyuqVuIwKlcNotnIxJp34FF2Fjns3oGnWG1loE8eGPfvzYsgg69dx6LfMxWrNbxGQkJCQkKh4qrzCqlQqadu2LevXr8+zf+3atfj5+VG/fn0AmjdvjpubG+vWrXO2sVqtrF+/ni5dulSJiM5RTZ9DLXNY/fQWA98f/alY5yv8/QGwGw2YExMKaV1+HE8+lWf7SFI03j0fIuyd99E2aIjcyxt1uCMozhQbUyEyubso8XV3+McIQKi/W4WMWxjuLkpeeLiBU6E+dSmZafP3M3vVMVIyjIWcXTYs+/cc7/10gK2Hb1TIeHcb6gdeRXC5yRYtyAA7ljPb0c1/AfO145Umm8S9y4kTx5kwYSyPPtqb++5rR9++DzBixFBmzcpNwbhy5XLWrVtTLuMbDAbmzp1DVNSBculfQqKsqXSFVa/X89dff/HXX39x/fp1MjMzndvJyY6Am5EjR3L8+HEmT57M3r17+fbbb1m+fDmvvvqqMy2WUqnkpZdeYsGCBcybN489e/Ywbtw4rl69yosvvliZl5iHD9u/7Xx/JPEEJxKji3yu0jd3idJw9QpZx4+VqWxFJcuU11JntJlINqSg8POj2mtvUH38JESlkqzjR7k0eQJxPy8ssCBEWdOxscNP1w50bVYNuUwkMVVf7uMWh2sJWYiCwMHTCUz+cQ//Rl3DVs5zE+LviqtGgShW/kNbVUQURbT9pzl8b8Hhq+tVzfHeZsWw4StMR9djs9watSYhUTJ27drBSy8NQ6fL4uWXR/PZZ1/z6qtv0KhRE/79d6Oz3apV5auwzp//A4cOHSyX/iUkyppK92FNSkri1VdfzbMvZ3vhwoW0adOGZs2a8c033/DZZ5+xevVqAgMDmTx5cp4qVwDDhg3DbrezaNEiEhMTiYiI4Pvvv69SVa4UCgVvtxnHu3s/AuC7owt4r/0EPNWF+9iKKpUziCXh54Uo/PwIe38mQhlWkiiMDEMGtuyI6zC36lzKuArAicRoOoW0QxAE5Nn+wvps9wxBLkcQBGxms/N9edC+YSCrd1wEYOP+K2jVCv6Nus74wc2pFVw1UtH0aFWdyFBPfvrrNBdj0vl5wxl2H4/l2V51qebnWi5jdmkSTNemwVVilaGqImrd0fR8Hf26T8BqQh4YgdigB6Zjf2NPi8G4ZynGvctRNHsYdct+lS2uxF3OkiULCQoK5tNPZ+WJZbj//gd5+eXRJerTYnFk3ChubISExN1CpVe6ulso6yCRPTEHWHRqGQAyQcZX931QpPPOjBwBRqMjd6XNRsgb49DWq19mchXGvONLOBh/GIBPOk9l7LZ3AKjtUYvXW+S3ZOvOnEYdWgNRrSZ2wTwsqakEPDUEhW/5BLS89d0uElINKGQC9cO8OXI+iYH3hdOrTY1yGa8gihJYZLPZ2XzoOr9tPY/BZGXcE82oW8Or3GSy2ezEp+rxcVehkJcuF15pqGpBV7divnQIw4avADuqzkNRRHbCHL0d4/YF5GQrUDTsgarN4wgyxZ26KjZVfW4qk8qeG7PZRFJSDD4+QSgUylL3N2TI42g0Wr7/fsFt2wwY0JfYW1yqAgODWLFiDVFRBxg9+kUmT36H8+fPsnHj3yQlJfLzz8txd/dg7tw5HD58kLi4WFQqNbVqhfPccyNo0qQZADExNxg48OF8Y/bq1YdJk6YBcPXqFebOncOBA/vIysokOLgajz76OI899niecy5cOM+sWZ9x9OhhNBoN993Xg3btOjBu3Gt89dV3NG/ekgULfmT+/B9Ytux3AgLyppecMeMdduzYxqpV6/IETJcFcrkofZduQ0XNTWHfnbuq0tV/lbZBLdlz4wBn0y5gtVuZf2IJQxs8Weh5Mq0Wq9EINhvqWrUcFtcK5ELaJQAUohw3tRtKUYHJZuZSxpUCq4lpIxzWbXNyMhl7dmG3WLj09iR8HumP1/0PIMjKVnnq0DCQ1TsuYbbaaRzuQ5dm1Wha2xe73e5I7l9FrIyiKNC9RQjN6vhy5FyiU1k9cdGRy7ZBWNnG90/+cS+xyTrGD25ORHXPMu37XkIR1gxby/6YDqzEuP0nEESU9bogegSg3/AVmHTYkq6S9fsMFNUbomr1WGWLLHEX0rBhY9asWc0XX3xMjx69iIysm88yOmPGx0ye/Baurq6MGTMeAKUy70PSnDmzadSoMWPHTkAURby8vEhNdVQWGjp0ON7ePuj1erZt28wrr4zgiy++oXnzlvj4+PLpp7N4441X6NPnEfr06QeAl5fjPnTx4gVeemkYAQGBjBr1Gj4+Puzdu4cvv/yEtLRUhg17AYDExEReeeUF1GoNY8dOwNPTi02b/ubzzz/KI+cjjzzKwoXz+P33lbzwwsvO/enpafzzzwYee+zxMldWJe49JIW1EnmtxYt8sv9rLmZc4UDcYTyV7vSv0+eO58h9/bCmpCCo1AS/8hpyt4pd6k41OtKLVXMJBkApU2KymbHYLNzIiqWaa1CB5ym8vakx7T3iFi5Af+Y0icuXkrF3DwFPP4s6rGaZydci0p/VOy4BsPN4LJOfbonZYmXRhjNolHKeuL9qJIfPwdtdzX3NQwDQGy3MW3eKlAwj7RoE8L/udXDXlt6aA+DvpSE2Wce1hExJYS0EZbM+WC5FYUu8hHHbfGR+tZAH18Xt2W+wXD2G5foprEfXYUq8iC09DlXbJxBdys86LnHv8eKLo7h8+RIrVixlxYqlyOVy6tWrT/v2nXnsscfRarVERNRFpVKh1brQ8DYpDKtVC2HGjI/yWMrc3T0YO3a8c9tqtdK6dVtiYmJYsWIpzZu3RKlUEhlZDwA/P/98/c+a9TlarQvffPMjLi4OV6VWrdpiNpv4+eefGDBgEO7u7ixbtpj09HS+/voHatZ0VJls164DY8a8QkxMbpCnl5c33bs/wJo1qxk6dDgKhUPxXrNmNWazmf7987r3SUgURKUHXf3XebX5CFSi48ly09VtHI0/ccf2quzlFEEuQ+7mjt1ux5Kda7a8uZh2CXv2smjHkLYAuKtz/S5Pp5y74/nKwCBC3hxPwLPDELUuGK9c5sr77xL/62JshrIJjgr2dcHXw5Et4MKNdOKSdZy5lsaOozFsOniVG4lZhfRQeQgCNI/wQwD2R8eTpS+7IJ+QbP/YawlV9/qrCoIgonlgtLPErO6P6dgsjipi8uqNUDbthehXC1y8sZzfR9bS8WSteger1VRIzxISDjw8PPnmmx/58ceFvPjiKDp27MLVq1eYM+drnnlmEKmpqUXqp0uXbgXuX716BcOGDaZbt/Z06dKGrl3bcvDgPi5fvlhon0ajkYMH99G5c1dUKjUWi8X5atu2AyaTkRMnHAG/hw5FUatWuFNZzaFHjwfz9Ttw4CBSUpLZvNlRHc9ms7F69W+0a9eBoKDgIl2vxH8bSWGtZBQyBaObDXduf398IXrT7ZW3nPyrNp2O1G1buDxtCldnzqiQKPwl0Sud79sFtQSgS1hb575TSWcK7UMQBDw6diZs+ge4tWkHdjupmzZy6e1JZB4+VGoZBUGgVV1H+q8GYV4EeGtpEObNgK7hjHm8KcG+LqUeo7xQK+UM7hHBpKdb8tQDkQT5OGSNOpNAbHLpcqiG+Dn6uhafWWo5/wuIrt6oH3jFsWHSo/99Ru4xtRsu/d9G/cBoh+JqMWJLuIhu3ouYL0opgiSKTt269XnqqWeZPn0mq1f/xf/+9yQxMTdYsqRoKQ99fHzz7fv115/55JMPqV+/IdOnf8ScOQv48ceFtGnTHqOx8FR66elpWK1WVqxYSteubfO83nzTERCdlpbqbOvlld99qaB9ERF1adKkGStXLgdg167txMTc4LHH/leka5WQkBTWKkCYRyi9ajhKXNqx8/bumbdtq84ukIDdTuo/mzAnJmKOi0V/5nS5y5lqcFhy5UKuJ0mv2l2d78+mXsBqK1qidbm7O0HDR1DttTdQ+PphSU7mxtdfkrZze6nlbB7pCOg6fyMdc/ZS2UNta9Cgpjd6o4XFG86QWYbWy7KmVrA7nZs4LA7J6QZ+WHuSt+fuY83OiyUuhhDi77CwXk/MrJCHm3sBRWhTFE0fAsCWdAXD9rxKhMIvDO0jkxF9sot42G0YNn5N1poPsBmkBwOJ4iGXyxk61OEbeuHC+UJaOyjIJX/DhvU0a9aCsWMn0L59Rxo0aEjduvXR6Yq2uuLm5o5MJuOhh/ry448LC3y1a9cBcLgfpKQk5+sjOTmpwL4HDPgfx48f5fTpaH77bRnVq4fSqlWbIsklISEprFWEPuEP0NS3AQA6q46JO6YX2E4VUt35Xu7hgVsbx5c9bduWcpdRZ3VY+SK9azv3qZVq3BUOZchsM3Mp/Wqx+nRp2Iga70zHq+dDKPz8cWvRyjHWqZPYbSVTzmoGuePpqsRgsnLyUhJZhlzl9Ic1J/kn6hpz11ZsJa7SUKeaBxarjVXbLzJt/n7OXE0tdh+B3lpkooDeaCUp3VD2Qt6jqFs/jhjg8Hs2n9qM+dyePMcFUcTlsXdR9x6HoPUEwBZzmqxFr2KK3lbR4krcJSQmJha4/9Ilx5K9b3YWFYVCWSSraF6EfNHY586ddS7j55ATwHVr/2q1mmbNWnDmzGnCw+tQt279fC8PD08AmjVrzoUL57l4MW8lyk2bNhQoWefO9xEQEMjXX3/OgQP76N9/oJRuT6LISAprFWJ442eQC46o+TRTOr/etASfgyiXI88uM+vdqzeene8DIPPgAayZ5WfVORh31Pn+gdD78hxzUzmqSgkIJBtSit23qFLhN+Bxarw7HVGtRhd9imuffsTVjz7Anp1bsFj9CQLNIhw3/B/WnGL2ytwb9aOdaxHgpaF3+7Bi91sZeLuref3xJrzQtz5uWgU3ErP4cHEUv/5ztlj9yGUiQT5aQPJjLS6a3m+B2vEZN2z+HltGfuuRolp9XJ/6AkXTPtm5kq0Yt80j85c3scZfyNde4r/NG2+MYuzY0axatYKoqAMcOLCPX375mUmT3kSj0TJw4BMAhIfX5vz5s/zzzwZOnTrB+fN3jhMA6NChE/v372Hu3DkcPLifVatW8MYbo/L5iWq1LgQGBrFjx1b27dtDdPRJZ6DUq6+OJS4ulpdffp516xxptHbs2MbSpYsZPTo3feHjjz+Ju7s7Y8eOZv36tezZs4v33nubK1cuATgL++Qgk8l49NGBHDp0ELVazUMP9S3NNEr8x5AU1irGBx2nON9vv7GHi2lX8rVR+jkUVl30KQSlElVoDewWC+m7dpabXH9d2uR8X9srb1S/rybXX6lVYLMSjyFmWwUsaakIKjWqaiEIcjk2gwGbqXgBLS2yFVad0UL0lVSnD2iIvyvvD29L7WoeZOrNRF8uvoJd0QiCQNsGgbw/vC2dsqt5ebkVPwVMTuDV9QRpubo4iHI5Lv3edgZhGbbPv631X916AC5PfIoszOHjbc9IQLf6XXR/fVmRIktUcZ5++jnc3NxZunQJb701hrFjR7Nixa+0bNmaH374ifDs0tbPPTeCpk2bM3Pm+wwf/gxvvfV6EfoexqBBT7F27e+8+eZrrFmzmrFjJ9C4cdN8bcePn4JarWb8+DE8//zTzJv3PQA1a9Zi3ryfqVUrnB9++JYxY0bx4YfvsWXLP7TIXgUDhyV41qzvqV49lI8//oB3352CQqHguedGAODqmr9EdvfuDwDw4IMP4epaPsVSJO5NpMIBRaQiE1afTT7PF4fnAI6iAp90fgelLHeJJ27xItI2/wOAR+euqEJDiV+8CI+u3QgYPKRcZHpr2zQyLTo8lR6833ESkJvMe1nUOlacdZQPnNDqVfy1/ihLmVTdnJyMqFYj02qJW7wQ3fHjBDz9bJGLJFisNl6ftYMsg8NC27N1KI93y3VlSEozMHNJFBk6M5OfblGmVabKO8n5+etphAW5IRNF4pJ1LN9ynkHda+Probnjeev2XGbFlvO0rufPi480LHO5ikJlJ4AvDZbES+j/mAEWE8qmvVG1vnMqHlP0Nozb5gN2BK8QXAcW7OaTw908N+VNZc9NWRcOKEuqYnL8mTPfZ9Omv1m37h9nCqscVqz4lS+++ISFC5dSq1Z4ucpRFeemqnA3Fg6QLKxVkDre4fQP7w2A1W5l2u68SZitGRmON4KAIJfh3rY9NT/4qNyUVbPZTKbFYaGs650/j2nHaq2d7z/Y/yVnCklvVRQU3t7ItFpsBj1ZRw5jTojn2qcfETP3eywZhafxkstEmtTOjaDdcSzGGYAF4OmmxM9Tg7uLgrvtiS28mgey7KW2xZvOEHUmgck/7mXbkRt3PC8nU8B1ySWgRMh9w1B3HgaA6fCfGPYsvWN7Zd3OaJ/9GrFaA7QPvQFAxk8jHW4CesnKLXFvMH/+D6xZs5qDB/ezY8dWZs58n7VrV/O//z2ZR1k9cyaarVv/ZcGCH+nUqUu5K6sS9x5S4YAqyv01uhCdcpZTyWdIM6Xz4b4vGd/akVJE4ZetiMkV+D/pUFJFtSP3aEHVpkrLHxf/cr7vVaN7vuMaZV7LXlIJ/Fhvh6jWUOOd90latYLUzf+SsXsXWceO4jdwEO7tO9zxWltE+LHreCyCAJl6M4fOJtC6nsOdQiaKvNTPYWV01ShI15lw1SiqTCWsovJE9zr8ZD7NmaupaFV3/jrXrubBm4OaUs1fWoYrKYrabTFfPoT1/F7MR9cjC6iDombz27aXKV1w6f0mAMZDa8GYhd2Yhe63SWjuH4U8sGoVspCQKC5yuZwlSxaSkBCP1WolJKQ6r7zyutMPN4eJE98kOTmJxo2bMnbshEqSVuJuRlJYqzCjmj7PG1vfxmA1cDXzOotPLmdw/YGoa2T7kJpNmGJjkLm6IarVJK//k4x9e6k+fhIyl7LLN3oyOTdllq+LT4FtVDIVRqsRF7mWLiHty2xsAJlGg/+TQ3Br2564hQswXbtK3PwfSd+9k4Ahz6C8pTZ1Dg1qeqNUiJjMDsvqtiM3nAorOBRVgLPXUvlm1XG6NA2mX6daBfZVVQnycWHck804cTGZhjUdvsRnrqZy8HQC/TvXRK3M/Ypr1QrqlXHJ1/8i6i7PkXX1GJh0GP6Zjex/HyK6+RV6nrxxL6w3TmK9EQ26NPR/vA9qN7S930SWkxpLQuIuY8iQoQwZMrTQditWrKkAaSTuZSSXgCrOO+3GOd/vit3P2eQLaGrn+mJemjyBzKiDIJORcfAAppgbpO/ZVaYy6C2OQgahriG3bVPNxREMpLcaSDGkYrAUNxVL4WhqhVNj8lR8H3scQalEH32Ky1Mnk7T2jwKzCSgVMhrVzFWwT15KIT4lfwL++BQ9aVkmos4kYrYULY9sVUIUBBrV8kEQBKw2Gz/9Fc3GA1eZ8uNeDp/Lmz7nz92XmDZvH/uj4ytJ2rsfUa5E228KCCLYrGSteg+brfBsFjKZDG3vcbgO+QpFZCfHTkMGut/exnx+n5QfV0JCQuIOSAprFcdV6coz9XKXVn44thDc3XIzRstkWLMyHRWkOncBIH1H6ZPv52A0G0kzOXxmO4W0vW27Rr6OYCib3cbkXTM4nlg+eU4FuRzvXg9R453paBs0xG6xkLR6Jcnr/yywffPsbAEqhQxXjaLAilEdGgXxXO96TBzSHIVcdlcrDjJRZFD3Ovh6qElKN/LViqN8s+oYaVmOLAvJ6UauxGdyKbZiyvneq8g8g1B3ed6xYUhH/+fHRT5XULui7vIc8gb3O/cZ/vmGjFXTyTwrVcq6Fas+E6v17nuQlJCQKFskhfUuoHVQM3qH9QAgy6pj6enVCEpHtJ1nt/vx7uUI0HJv2w6ffo9S7dXCU58Ulfknlzjft/Rvett2nYLzViuJLoPAqzuh9POn2mtvEDh8BKrQGnh271Fguya1fZCJAkazlXFPNqNxeP5ShuBQWtVKOccuJPHB4ij0xuLnf60qNKrlw3vPt6FXm1BEQeDA6QTm/ul4gOjUJIhRjzbi/hbVC+lFojAUEe1R1O0MOIoFGPf/VqzzNR2eQvvMbJTNHwFRjjX2LPHLPiD9t/ewWYqXxu1exXh8E7pFo8hYOrGyRZGQkKhkJIX1LuGhWj2o7lINgF0x+5C5OAJnTHGxWFJTsFutyLQu+PR5GLmnV5mNe7PiqZTfPp2LRqlBI8sNvopOPlvulkpBEHBv047QKdPAZiPjwH4Mt1Rc0aoV1K3hmI+j5wsuF5iD2WJlwfpozl1LY/3ey+UldoWgUsgYeF9t3nyiKSqlDLvdEZAXFuhO8wi/EuVxlciPuvMwRG+Hq4zp0BosN4pXIlmmckHVsj+ah8ZCdtEQa9xZshaPwXzlcFmLe9dgTbpC5pI3MO36GQB7agyGhGuVLJWEhERlIimsdxGdqucuyaeoHEtkupMnuDD2dUw3rjuPmRMTSFy9Eqsu//J3cTHbHGVNXRXaQtt6qt1z5TOmkqC/s4JYVgiCQNKfa4j5bjZp27fmO57jFhB1JoHkdAO7jscU2I9CLuPlfg25r1k1+ravWWCbu42I6p7Mfr0zb/yvKYIgYLPbWbzhDB8ujspTslai5Gj6TYbsTBmGHQuwm/TF7kMeXBf3F+agrZv9HTdmYvjrCzJ/m4rVWPrv8d2E6fR2dL+9jT0z9/6hbNILtd/tfeglJCTufSSF9S6iQ3AbRBy+q5eCHNZOUaEAQcAUF+dsd33WlySv/YOMvXsK7KeoxGUmON93rlZ45L+fJm8GgdMpxSsfWhpc6jdAGVwNhW/+aO1mdXwRgAs30hn33W7mrj1FQmrBSkV4NQ+GPBiJQi6y71Qcxy9WjNJdXgiCkCdVlygIHD6XwJmrqVI+1jJClKvRDngfQevpsARunVui1QWZTEngY2/i/tSniJ6OMpp2XSr636ZgunDv+7aa4y9is9mQ1WwD5H5m5bVao20/qPIEk5CQqBJICutdRp9aDwJwxsvh4ya6uFL76+9wa5lbLs+joyMCOW3bllItyy849Yvz/YOh3QptX801KM92dHL5+rHejEujxoS9+z7eD/XJd8zTVUV4NQ8A/D012IHtR++cZP/g6Xi++/0Ec34/QXK6oTxErjDOX09j4d+n+Xufo8xvTlWvq/FS8vqyQubqjabHKBBlWC4eQL9xVsn7cvfD5fEZKFo+hqBywZ6ZhHHT12TMHY756vEylLpqYLdZyVwxBcPqdzBum48oE8HDkX5O9ApB3eW5Ms8tLSEhcfchKax3Gd1DHUEeaa7Z/m6pKQgKBTZjbhop93YdEORyjFevYLx8qcRjXc/IVerk8sJT9nau1i7P9tmU89jsFVcWz2Y0knX8KPrz+RXlHLcAmej44dt+NAbrberBAzQO96VWsDudmwbj6Xp3+3vGp+rZcug6B047UlmFZCus1xMkhbUskQXUdgRQAdZLUY5CAaVA3bwvLo9ORV47+3tlNWP4+wtMJ//FXoHfq/LEashAt/pd7MlXAbBcjsJ0eC2kxYJSi+aBVxAUd/f3ryozbNhgOnZsSVRU0Sz4Q4Y8zvvvT7tjm9TUVDp2bMm6dXnzrlosFn77bSnDhz9Djx6d6datPU899TgLF84jI6d6I9CxY0uWLFlU7GspKXPnzqFHj07O7ZiYG8ydO4fExIQ7nCVRGZSocMDZs2eJiooiLi4Og8GAl5cXtWvXplWrVri6SlV0yhO5KEctU5GpMWADRIuFi+PHYs3MpPasbxFkMmSurri2aEnG3j2kbduCOqx0/pghLkGFNwLcVe4oRQUmmxmZICPLouNaxg1C3SvG9yzl7/Uk/bEa15at0YTXznOseYQvyzaf40ZiFq4aBWmZJo6eS6JZRMEJ3xVykbeebI5C7nimO3kpmXo1vO5KS09YoBsAV+MysdnshPg7ikpck1wCyhxls76Yz+7CnhaLaf8KZAG1kQfXLXF/glyFptsIjF7VHIqc2YBx1xJMUb+j6vA0ipotylD6isOmS0W//jNsulRE/3BIj0f0q4m652uIViu25GsoIjsjegQU3plEibh8+RJnzjiCBDdu/IvmzVuW21gmk4k333yNo0cP0a/fAIYNewGVSsW5c2dYuXIF165dZeLEqQB89918AgOL9ptTFvTt24/27Ts6t2NibjB//g906NAJ3wJczCQqjyIrrGlpaSxdupSlS5dy48aNApea5XI5nTt3ZsiQIbRr166AXiTKgodr9mTZud+xC4AdrOnp2C0WTHGxqIIdmQQ8OnclY+8e0vfuxe/xQYhqzZ07vYUEXSJWHFacwfUGFvk8tUyNyZYbzBOdcrbCFFZtvQYk/bEaXfRJ7DYbgpi7gODvpSXEz5VrCZnUDHLj2IVkth65cVuFFXAqqz9vOM2/UdcZ1L0OD7S6+9JBBXhrua9ZNar7u2K12XItrImZ5VLK97+MIAho+79N1s+vg8WIfv2nuAz+DFHtVqp+Vc36oGzyEOaT/2A6+hf2zCQMG2dhqd0OVfvBiOq7x1Bg3L8S05F1kF1sQR5QG0WnZxG1DrcdZDjcKyTKlQ0b1iOTyWjatAWbN//DmDFvoVAoymWsuXPnEBW1n48//pK2bXPjIZo3b0n//gPzWHgbNmx0x76sVit2u71Iq35Fwd8/AH9/6cHobqBILgELFy7kgQceYO7cuXTu3JnPPvuMDRs2cODAAY4dO8aOHTv45ZdfeOONN0hPT2fYsGE899xzXL58d6cGqqp0Ce2AXJBjUjgUDW39hoR/PsuprAJoIiJxbdYC38cGOCryFJPFpxw5JWXIiqVwykXHTcRqd2QxuJ5ZcER+eaCuWRNBpcaWmYnx2tV8x5tHOHKwWqyOh61jF5JISivcPzXAS4sAWKx35zKsKAgMeTCSrs2qoZDLCPTWIhMF9EYrSXe5f25VRFRq0fR5CxDAaka3chq2O7ifFBVBFFE27IG6+0sIGodyZzm3m6xFo9FvW1Dq/ssb89XjZMx9AdOhPxzKqkyJsmV/VE17gyA4gtWMd5fV3263YzRZK+1VmhiFHKvqoEFPkpmZwe7dO/McP3bsCMOGPUW3bu0ZMuTxfMdz+OOPVQwY0Jfu3Tvw6qsvce2We6/RaGTlyuV06tQ1j7Kag0KhoE2bXAPXrS4Bo0a9wLhxr7F+/VqeeOJRunVrz9mzDsvwrl07eOmlYXTv3oGePe9j1KgXOHMmGoB169bQtm1zUlNT84x3q1vDzS4BUVEHGD36RQCef/5pOnZsSceO5Wd5ligeRXpEWbRoERMmTKB3794FPoH5+vri6+tLs2bNGDp0KFeuXOHbb79l/fr1vPjii2UutATU945Ep45DY7Kiz0xF5uaWx1omCALBI18pcf8X0y85+hGLZ31r5FuPrdcdpWGntH6DABf/EstQXAS5HG1kJFlHj6A7eQJ1aI08x5tH+PHHzkucu55GRIgHZ66lsf3oDfp1qnXHfu9vGUJkqCehAY451hutaNVl83RfkdjsdnQGC64aBUE+Wq4lZHEtIQtfj+JZ3yUKR+5fC2W7JzDtXuKwhm6ahfaBV8um74DauA75EmPUH5gOrgK7DUv0FrKSr6Lp+Vqprblljc1mwbj5Byzn9zr3iX61HLJq3LHbLBg2zcYacxqbPh1tz7IrfFKe2O12Pvg5inPX0ypNhtohHkx5pvgK1fHjx7hx4zrPPPMcrVq1xdPTkw0b1tO5c1cAkpISGTPmFcLDa/Puux+QkZHBp59+iO6WVIk7d27no4/e56GH+tK9+wNER59k2rS8RR6io0+h1+to165Dia8zOvoUcXGxPP/8S7i5ueHvH8A//2xg2rRJdOzYhalT30ehkHP06BESEhKIiCiZG05kZF3GjHmLzz6bycSJUwkNDSuxzBJlT5F+ddevX18s83toaCgffPCBVE6vHBlSfyDbXXbgk24lI+Yql9+diqhWU33chHxtjVevIqrVKPyK7o9jzQ7qqOtdp1hy9ap5v1NhvZ4Zg5/WF5PVhEZeMUqRtl59h8J66iTePR/Kc6y6vyt+nmoSUg2EBbnjolFQN7TwIguCIBAa4IbBZGH+umgSUvVMeMpRxvVu4fjFJL5dfZxqfq5MfKpFtntEFtcTMmlau+DqXxKlQ9XoAayxp7FePIj10iFMJzejrH9f2fXf/GHktVqj+/09MGZhiz+PbukEZDWaouw0FJms8j+f5osHMWxfAIacoBoBZeuBqJrmfjeNe5ZijTkNCjWqNv+rFDlLzF3qTbNx43qUSiVdunRDLpdz3309+PPPP8jKysTFxZVly35BEAQ+/vhL3NwcD0A+Pr6MGZPXVeOnn+bSpEkzp/9pmzbtMBgMLFo039kmMdER7FmaZfeMjHR+/HGhsw+73c7s2V/SqlVbPvjgE2e7du063q6LIuHi4kpYdsxHrVrh1K1bv1T9SZQtRdJCS+orUhVumPcqWoWWdE8VxJhRmKwYr1xGUCqxW60IN8174qrfSP5zDR5duxHw1NNF6vt0yjnsOJaaHq/zSLHkclPm+tKtPr+exadX0CWkA4+E9ypWPyVFW78BAPqzZ7CZzY48tdkIgkDzCD/+3neVdJ2JVx5rXKy+M/VmTl1OQW+0cO5aGvXCvMtU9vLEy02N3mjlSlwGNpudan5S4FVFoO4+Et3ScdgzEjHu/w15aGNEV5/CTywiMs9A3J6ZjeXaCYx7fsGWfA3LmR1Yzu5C038qct8ahXdSDtgtJkwn/8W051fnPnnNlii7jkB203fSfHYX5uMbAVB3HY7MK7jCZS0pgiAwYXBzTObKcxVSKsTsVbWiuwZYrVb+/XcT7dp1cAZJP/BAT1atWs7WrZt56KG+nDx5nObNWziVVYDWrdvi4uKSp5/Tp0/x8suj8/TftWv3PAprjttCaXzlw8Pr5FF4r1y5THx8HCNHvlbiPiXuPkqd1mrfvn18/PHHfPTRR+zZU7pE9RLFo2Y9R1UcuRUSHruPsHffBzHvv1Rbtx4AGXt350l9dSeWRq8CQEDAR1N8pUwuOB5wsixZGK0mrqRXXElFZXA1ZO7u2E0mDHdIb3XkXFKxfVJ9PTS81K8hbz7R7K5SVgGCvLWoFDJMZhsxyTrqhHjSpn4A9WuUXRlfifyIooh2wHuIPqFgzES/8WvsFlOZjyMPaYD20WmIftkZQew29L+/h2HfCqz6ik1fZti7nMzlk7BlxINMgaDxQN1vCpoeo/Ioq9bEyxiyfW+VzfrelRkPBEFApZRV2qskSuD+/XtJSUmmQ4fOZGRkkJGRQVhYLfz9A9iwYT3gcAnw8sp/j7t5X2pqClarNV87b++8235+DkUzLi622LLmjpv3PpWWlgogRfH/xyiVwvrrr78yYsQIrly5wunTp3nuuef4+eefy0o2iUJo3NpRREAE1gmnUfj65buBaSLrovDzRxEQiCUlpUj95pRUVcmUJZIr3DMMAK1cw/hWrzGy6XMl6qckCIKAtp5jGUd36mR+2ap54OGiRG+0cOpSMntOxPLRkihSMoqmzNer4UVEdU+yDGa+WnGUc9cqz3+tOIiiQPUAhzXlcmw6EdU9GfFwAzo1uXssWncrokKD5oFXQOWCLeEiuj/eL5MgrFsRRDku/aeium8EYkAdsFowH16LbtEoDPtWlPl4BZH58+uYj/wJGQlYLx9B238arkO+ROEfnqed3ZDpKK5gNSGr3ghli/4VIp+Ewx0AYMaMd+jV6z7nKz4+jqioAyQlJeLj40tKSnK+c2/e5+nphUwmy9cuOTnvdt269dBqXdizp+CgraJw6++ah4cnwB1zpSqVjt8viyVvCer09PQSyyFRuZRKYZ03bx4LFy5k1qxZzJ07l3HjxjFv3ryykk2iEJS+ftiyg6LCz6Ryeeb7JK7M+8MkiCKhk96mxuSpKAMDC+3TYrFgy05nFelZu5DWBZOz/G+2WQjJrn5lsFRcNLq2nsMtoCCFVRQEmtVx+GweOpvI5kPXib6Syo5jxctm8PuOixw+l8iPa0/esQBBVaJGgGN571Ksw5/w/I00/o26VqRMCRKlQ3TzQ915KAC2xMsYN88pt7GUddqhfXgiyg5POffZs/IrH2WF1WrFmuYoDS14ZAdZaj1xGTAdmXe1As8x7PkFe0Yigpsfmm4v5klBJ1F+GAwGtm3bSqdOXfnqq+/yvN5990NsNhv//LOBevUaEBV1kMzMXOv8vn17yMrKdSGSyWRERNRl27YtecbYsuWfPNsqlYr+/QewfftW9u/PvwprsVjYt694q7OhoTXw9w/IV5zgZnIsu5cuXXTuu3DhHMnJdy63nRNYbjSW/UqIROkoknPqkCFDeO+99wgLC8uzPyMjg1q1ciOsw8LC8nzAJcofVbUQzFevojXaMZ49i1CAK5Ms20/Jbrdjt1jy+HXeyh8X/3K+HxhZPP/VHIJdHIpxpjmLlWfXsjfuIM39mzAosmKsKNp69RHVamQeHvnysYLDLWDL4RtEnU1kYNdwzl5LY9vhG/RuVwOxiEtsj3auRWKqgX6daiK7S35scwoIXMlWWJf+e45z19LQ9JXTzqPwhxmJ0qGo2RJzSCOs145hOb8XU3BdlPXKLgjrZgRBQNXgfuS+NTHsWozmvhewGTLJWvIGsuBIVD1eLZMYA9OZHRi3zgNRhttzP6B58HUsF/airNvljuep2vwPuyETVasBCCqXO7aVKDt27NiKXq9j4MBBBRYK+OWX+mzY8BcffvgZq1YtZ+zY0Tz11DNkZGQwd+4c3N098rR/5plhjB//BjNmvOPMErBx41/5+n3uuRFER5/krbfG0L//AFq1aotSqeTixfOsXLmcBg0a0bp12yJfhyAIjBz5KtOmTWLSpDfp2bM3CoWSEyeOUbdufTp06ESDBg0JCAhk1qzPGDFiFFlZmfz880+4u7vfse/q1Wsgk8n488/fkclE5HK5FHxVRSjSL23t2rXp168fs2fPxmzONa+3b9+e119/nS1btrBu3To+/vhj2rfPn2dNovxQZTuiGxUCm9p5EPD0swW2yzpxnCvvTSNx+dI79rfzRm7qGS+1Z4lkUshyFeJjiafIMus4nXK2RH2VaHwfH8K/nE21kaMLtNzUreGFRiUnPcuEl5sKrUpOUrqBkxeLboVSK+WMHtCY0AA30jKNbNyfP+9rVaNRuA8TnmrO6483BaBeqBeNw31w1ZRPsnCJ/Kh7vo7g4vDHM25fiCWxfHNVywLCcen/NgCGf+eAxYj1ylF0i1/DEpffx7uo2EwGdGs/wrjlR7DbwGrGdGYXolJdqLIKIGrc0fZ8HZnP3VeI425mw4a/CAgIpFmzgv2Fe/bsQ3T0SXS6LD755CuMRgNTpoxn8eKfGDPmLXx88gYMduzYhbFjJ3DgwD4mTBjL/v17mTbt/Xz9KpVKPv10Fi+/PJojRw4zZcpbjB07mtWrf6NLl26MHFn8lG/duz/ABx98SkJCAlOnTmLatEkcPXoYf3+HlV8ulzNz5icolUqmTHmLn39ewOjRY/D2vnPQo6enJ6+/Po7Dh6MYOXI4zz9ftGBlifJHsBcx8/Dhw4d5++23sVgsvPfee7Ro0YK0tDSmT5/O9u3bsdvtdOzYkUmTJuVzur4XSEnJwmKpeku/cUt+Ju3fTZyuruSvTp70CO1Kv9oP5WuXdeI41z//BFGrpdYnXyAqC/ZPHfnvOABUopLPuk6/49hyuYiXl0uBczN68wSsdisuMi06qx47dt5rPwFvdcUE+djtdsxxcVjS09BGROY7/v2aE+w5EceDratjsdr55+A1WkT6MbL/naus3IreaGHyj3tJyTAy7KF6dGwcdMd5+a8jzY2jLGnWkrGO5PkKNS6Dv0BUqst9bqy6VHSr3oOs7CVRUY6seiPU3V9ClBfdX12/+1csx/7GGZkuV6Hq+AzKiDsbK6zJ1zEf34Cq/ZMIclWxZK/sz43ZbCIpKQYfnyAUipL59pcXcrn4n/0uFYY0N7enouamsO+Ot7cLMlnRVimLvJbZtGlTVq5cySOPPMLzzz/P22+/jUwm4+OPP2bPnj3s3buXTz/9tNyU1U2bNjFw4ECaN29O+/btGTVqFBcuXMjXbuvWrfTr149GjRrRo0cPFi9eXC7yVBVsWQ4XjJB4M/XP63FZ9AcZUQfztdPWq4/c1xebTkfmwf0F9pVpyHXnaOzXoFRyBbs4LL8Gm5Ea7g4ryunkklt0ikvWkcNcmjye+EU/FXi8eR1HdGnUmQQ6N3H42R4+m0haZtGCr3LQqOR0aRJMsK8LtUM8Cj+hkknJMHLwdIIzvdXV+Ez2R8dXtlj/KUStJ5qerzk2zAb0v79XIePKtJ64Df4U9YOvIrj7g82C9fIhsn5+DfPZXYWebzdmod+2AMuxv8hRVhX17sPl2W8LVVbtxiz0G7/CHL0V4547r/JISEhIFESxnO/kcjkjRozg999/5+rVq/Ts2ZN169aVl2xOdu3axahRo6hZsyazZs1iypQpXLx4kaFDh+bxmT106BAvv/wy9evX54cffqB///5Mnz6d5cuXl7uMlYWymqNsqtoMvikWalw3kBF9Il87QRTx6NgZgLRtWwvsa/2VXGf50vqbNvdvAjhKtEZ4OiKEoyvQLUBTJwJBqUTm7o7NnN95vlEtHxRykYRUA3Y7hAe7Y7XZix18BdCnQxhTnm5JoLeWhFQ96VlV11n/z92XmL3qGLuOx2IwWZg6bx/frj5OlsFc+MkSZYY8pCHK5g4fcVvKdQw7FxVyRtmhqNEM7eMzkNduDwhg0mHY/D2Zv7zpDJ66GavVim7j12T+8iaW6C3ZnWjQ9nsbdadnEAvx4bbbbeg3f489LQ7B1Qdli35lfk0SEhL3PkVWWO12OxcvXiQ6OprAwEDmz5/P2LFjmT59Oi+88AI3btwoNyH//PNPgoODmTlzJh06dKBXr1588MEHxMbGcvBgrjVx9uzZ1K9fnxkzZtC2bVtefvllBgwYwJdfflkuaWSqAuqajqA3mc3O2epKNrdw5U+fglN9eHTsBKKI/uwZjDeu5zt+NMERVa+SKVHL1aWSq1VAc+f7nPRYp1POlar2dXGQubgQ/uVsqr85HrGAZQiVUkbDmo7VgKgzCXRu6kjvtOdk/h/swhCzczGevpLCuwv2M3vlMazFzPFaUdTIDry6HJuBVq3Ax92xNHtdKiBQ4aha9kcW5MiTbD61BUt8/hWj8kIU5Wi6vYDm0XcQsgsZ2DMS0C19C9OpLc52toxE9EvHYb14AEw6BHd/NH3ewm3ot8j871zSOAdT1B9YrxwBmRxNj1cQNXcOepGQkJAoiCIprOfPn6d379706tWLfv360aVLF7Zs2UK/fv34888/8fb2pnfv3syfP79cFEOLxYKLi0ueXGw3V+AAMJlM7Nmzh969e+fZ37dvXxISEjh5Mn+Ko3sBTc3cHw1BpeZopJbDioKVLrmnFy6NHZZP/enofMdTjKkABGlLHzHupcldHr+ScQ2FqCDDlElMVvEVwpIiKhSYU1LQnz1T4PGcIgJRZxJpXTeAwT0iGD+4eYFti4KbVonFZsdotpKpr5oWy5qB7vi4q/H1dDyQVPNzZJC4liBl96gM1L3HIq/RDGxWMv/6CmtWxeb1lfuG4vrkp8gjOjn3GbcvQLdxNrpN32LcuxR7psPnVXDzQ9tvKvLgekXu33L5EKaDqwFQd3oWmV9YieSsqAddCQmJqkuR0lpNnTqV0NBQFixYgFar5bvvvmPcuHHs3LkTLy8vPvzwQ/r168fUqVNZs2YNK1euLFMhBwwYwLPPPsuiRYt45JFHSE9PZ+bMmYSHh9OuXTsArly5gtlszpNmCxwZDsChdDds2LDEMhTVKbjCcdU6qlvZbNxPTQ6fPk5wopmDAf/Spsn9+ZoHPv44wpNPorylrnN8VoKzHOv9YZ2Qywu/3pw5ud3cqGQqjFYjVzKuU8erJieTznAm7RyhnhWTrF539gyX3p+O3NOLOp9/kS/5dIu6/sxfF821hEwyDWYebBNaqvFCA92Y8FRzagS54+GqIj296llZw4Ld+Xx0br3t0AA3jp5P4kZiVpH+56WlsM/Mfw8Rxf0jSP9tGrbUWK5+9wrazs+gqF30FD9lgdv9w7G26of+4B+YT2/HFncGuy4NZYP7kIc2Rt1mAIpiKpvW1Bj0m78HQNXofjT1OxdbLpsxC/3uZZjO7kL18KvIgotXTrmssNlKXla0PMm5pQkCSDp9XqS5uT2VMTcymVDq35giKawnT55k9uzZznQRI0aM4Mcff+TatWvUrOkoBdi2bVvWrFnDt99+WyqBCqJVq1Z8/fXXvPHGG0yf7ohcr127NvPmzXNWs0hLc1gmbs2xlrOdc7ykuLtrSnV+eSLTaLBmZVHX6obhspGgRDP/7v+Tnl0LyKPqFVFgHwujc2t+P1C/Y4Ftbsft5ibIzY9LqdfINGfSPOQ+Tiad4XzGRQZ69SpW/yXFo2kDriiVWFJTUGeloq0ekue4lxc0DPfh6LlETl5Jo264w+Kqy/bn1KqLn+6phZcLVquNjXsvs+3wdaY937ZKK2eRNX1Yu+sSMcl6vLwqLh9mVf4+VTwuuAwcx/Ufx2IzZJG54RuUR/8i8H8TkbtWYOlcLxcIG43hxkPELJ4GCKg1Gnz7TS1Rdzf+XAgmPerq9QjqPRxBVqSfG8BhUc2K3k3S33OxZqVm77NV2ufGYJCRmCiWyY9ueVCV7zGVjTQ3t6ci5sZmExBFEQ8PLWp16VwNi3QHqVGjBn/99Rdt2rRBFEXWrl2LQqEgKCgoTzulUsmrrxY/n1phREVF8eabb/LYY4/RrVs3MjMz+e677xg+fDi//PILrtmJ8SF/CbfC9heV9HR9lfVLlLm5Yc3KIuPyNa7XD+BCWgrXPOxcjYnDVe2ar701M5OULZsxxsRQbfgLAOy5eggAhSgnJaVo/owymYi7u+a2c1PHozaXUq9htlkIVdcA4FT8WZKSMxCFirmJaOrUIevECWJ278e7gB//prUdCuuOw9e4r2kQa3Ze4vcdF3isSzi92tYo0ZhGi435a0+SoTPx5/bzVa786dHzSWw9dJ1awe40ru2o+nUpJo3k5MxSf08Ko7DPzH8WhS+e/5tOxrrPsKYnYoq9wJWvXkDd4hE0rSu4bKkmCM/n52CzWRCLcT+4FVXn57BuX4Sq61BS041A0TJwWDMS0W/7CfPlIwCInoG43jcM13otKu1zYzIZsdlsWK32KpUmSRAc3ymr1SZZEW9BmpvbU5FzY7XasdlspKXp0Out+Y67u2uKrDgXSWGdOHEio0aNYs2aNSiVSrKyspg0aVKpteWiMn36dNq2bcukSZOc+1q0aEHnzp1Zvnw5Q4cOxcPD4TN5qyU1p25wYdUtCsNqtVWpG9XNyLx9IDYWS1oqvUa+xeTdMwCYc3QRrzYfka+9Wacn/rcVYLfj1asPysBArHbHB8lV4Vrs67zd3HQObsfGy1sA0JkMDG/0NHU8a2Gz4iz/Wt5o6tYn68QJMk6cwP2+/C4STcJ9gdOcu5ZGYqoerUqGyWzj36jr3N8ipEQKnEou8kzveiSl6GgZ6VflPjdJqXr2R8eToTPRvUUIMlFAb7QSl6zD16NiLFhV+ftUWci9Q6jxyhxubFiM4cBqsNswHFiF8dRW1D1fQ+5TOpeV4iOWLiZB4436gVexAbYi/K/tNivm4xsxHlgJFhOIMpRNe6Ns2gdZ9m9NZX1urNaqqfHkKBuSQpYfaW5uT2XMTVk87BVJrW3VqhWbNm3iiy++YPr06WzcuJFBgwaVauDicP78eerWrZtnn7e3N/7+/ly5cgWA0NBQFApFvtys5845cn+Gh4dXjLCVgFsbh7+bzNUND7mWFuctdN2fwbWM/JkAABTePrg0cviCpW3fwrWM3FROj9d5uMzk8tZ4IRcc5R8Pxx+jqV9DXBRarLb8T1nlhbaeo6Se/nQ0dmv+cb3cVNQMcscOHDqbSOt6AagUMuKSdZy5mlricR9sG0avtjVQyGWkZBQvt2t548wUEJeJTBQI9NECcE3KFFAl0LTq5ygm4BsGgD0rGf1vb2M8+hd2e9VW8i3XjmPYtRi7zVKs86wJl9Ctfhfjnl/BYkIWGIH2sXdRtXwUoRhFDSQkJO5dirwu6+bmRufOnbn//vsJDKzYuuPBwcGcOJE3t2hCQgLx8fFUq1YNcLgjtG3blvXr1+dpt3btWvz8/Khf/96tBawKcsyBOTEBQZTR4WA6Tc7qUaZkciQhf05WAM/7H8Dn4X54du/Bzht7AFCIChr7lzwwrSBkosOIfyzxJJfTr/LR/lnMOvxDmY5xJ1ShNRC1Ltj0egyXLhbYpkVkbhEBjUpOm/qOgLStR0qXqi09y8Snvx5i6rx96I3F+wEvT4J9XZDLRPRGC/GpeqpnZwq4LmUKqDKIWndcHp2GutuLkK2wmfb8iv6PD7CmFPwgWtnY0uPR//Mt5uMbMR/bUKRz7GYDht2/oFv9DrbEy6DUour0LJq+45F5VStnif+bzJ07h44dW9KxY0s6dWrFgw924ZlnBvHZZzO5dJt7ZFmxbNkSdu/eUezzRo16gXHjXiszOZKTk+jRozNnb8kgo9frWbhwHkOHPkmPHp3o1q09gwY9ypdffsq1axVbfjsm5gYdO7Zk8+ZNd2wXFXWAjh1bEh3tyIRks9l44olH2bBh/R3PuxspksJ65MiRYndsMBg4e7ZsEsUPHjyYf//9l3fffZedO3eyfv16hg8fjlar5eGHcy2CI0eO5Pjx40yePJm9e/fy7bffsnz5cl599dVCk1vfzSj9HAqXJSUFm9WCV9f72F9fi0UmMP/EkgLPcanfAJ+H+6Hw9mHHjb2OfXJtmcvmq3bkOk01peOi0HI54yoX0i5jtFZMcn1BFNHWc6Th0Z0qOLVZTnqr6Msp6AxmumTnZD0QnVCq9FQuGjlJ6Ub0RkuprLVljVwmUt3fEWB1OTaDan6O96kZVbfgwX8VRe22uDz9DcrWj4NchTXuLLoVU8j6/X1shqpjEbdbjOg3zgJjFqJfLRQN8rvf3IrlymGylk/CfOxvsNuR12qNy+MzUNbrilBBPu7/VVQqFd99N59vv53H9Okz6dWrDwcO7GPo0Cf5++/yKwa0bNkv7N69s9jnvfHGeEaNeq3M5Fi4cB7NmjWnTp3cIOTU1FRefHEoixf/RLt2HZk+/SM++eQrBg78H4cOHeTFF4eW2fhlSWRkXb77bj41ajgC4EVRZPDgp/nxx++wWKqOoaQsKJIP61NPPUXHjh0ZMmQI7dvfuQRfYmIiq1evZsGCBTz99NPUqVOn1EIOHjwYhULBkiVLWLVqFVqtlkaNGjFz5kxn5gKAZs2a8c033/DZZ5+xevVqAgMDmTx5MgMHDiy1DFUZ0dXVmZ9CH30K/0GDObnzIpnGdLCZ0Zl1aBUFK6P6uDgiz2dxqpYG19u0KQ2R3nW4nhWD1W7FV+PDsAZPUssjzFlMoCLQ1qtP5sED6E6ewKdPfpeHQG8twb4u3EjM4si5JNo2CCDU35Ur8ZnsPh5Lj1bVSzSuTBR5rk893LVK/DyrVlR8jUB3LsZkcDk2g97tatCteQgaVdGjuCUqDlEuR9X0IRS126DftgDbtWPY4s6S9fNolK0Homrcs1Lls9vtGLbNx5Z0FUHjjqbHqDsu49t0qRh3LcZywVEiWnD1Qd3xGeShlZOy6r+IKIo0bNjIud2qVVv69x/IuHGv8eGH79GwYWOqVQu5Qw8VS82atQpvVER0uiz+/PMPpkzJWxL5k08+4MaN68yZs4BatXJdCJs3b0n//gP5449VZTK+0WhEpVKVSV8ALi6uef6XAN27P8gXX3zCzp3b6dLlvjIbq7Ip0mPsn3/+iSiKDBs2jE6dOjFmzBh+/PFHVq1axbp161iyZAkzZ87kiSeeoGvXrsybN4+RI0fy/PPPl4mQgiDwv//9j99//51Dhw6xc+dOvvvuOyIjI/O17dKlC7///jvHjx9n06ZNDB48uExkqMoIgoAgdygbhkuXsGZmMsLcgsZndAD8El1wXlxLRjpXpkzggT0ZeGRYeKLugDKXrVv13ITk0cnnaBHQFC+1J7YK9MVz+rGeP4fNWLA/aW4RgQQEQXBaWbceuVGqpOXhwR74eWpITjew71TFFU0ojOYRvjzcIYxmEX5o1Qo0KjkmsxWbTYpQqKqIrj5oer6OolFPxwOqzYppz69k/joOW2pspcllPr4By7k9IMhQ3z8S0dW7wHZ2uw3TyX/JWjbBoawKIorGPXEZOENSVqsAKpWK1157E7PZzNq1vzv3r1+/lpdeeo5evbrRs+d9jBr1AidPHs9z7ty5c+jRoxPnzp3lpZeeo3v3DgwZ8jh79+52thkwoC+xsTGsXLnc6ZKwbt0a1q1b49y+9RUT43DLKsglYOvWzTzxxKN069ae4cOfJjr6JD16dGLu3Dl3vM7Nmx0lyNu2zTW+xcbGsHXrv/TvPyCPspqDKIr06/eYc/vWZfgcxo17jVGjXsg3LydPHmfEiKF069ae335bCsCRI4d46aXn6NatAw891J333ptCcnJSvrENBgMffPAuDz7YhV69ujFr1md5LKcFyaLRaGjbtj1//bX2jnNxt1Ekk0poaCizZ8/m/Pnz/PLLL2zdupV16/IuG6jVapo2bco777xD3759nflRJSoGUavFmpaG6fp1zMlJGH5eSnuFyNE6Go4mFrwULndzJz7YlYBr6TS8YCTskZJZEu+Elzq34tX2a7vwVLmx9PRqjFYT41q9UubjFYTCPwC5tw9gx5yYgKoAy0GLCD/W7rrEsYtJmMxW2tQPZOnmc2jVcrIMFlw1xc/JmkN8io4pc/dht9upFexeYZH4d6JhTR8a1vRxbr+/8AAXYtKZNrQ11f3zp0KTqBqIooi63SCUjXqgX/8ZtpTr2NPjyVo2AUXdLig7Pl2h7k+WG6cw7nH8AKvaDUIelN+IAGBNvo5h+3xscY4gWNGvpqPylW/JUsdVFex2uyOjQWVRxgFpNWvWws/Pn+PHjzr3xcbG0LNnb6pVC8FsNrNp01+MGvUCCxb8Qmho7v/PYrHw3ntTGDBgEM8++zyLFs1n8uRxrFixBg8PT2bM+Jg333yVRo2aMmjQUwBOK+53383PI8dXX33KjRvXcXMrOLvPmTPRvP32eNq378To0WOIjY1l6tSJRVoCP3BgH5GR9fLoKIcPR2G322nVquwLdpjNZt59dwqPP/4kI0aMxM3NnejoU7z22ss0btyMd9/9gIyMdL77bhajR7/E3LmL8lhg58yZTevWbXn33Q85cyaaH3/8DrlcwUsv3fn3s1GjJsyd+z1WqxWZTFbm11UZFGsNMDw8nMmTJzN58mSSk5OJj4/HYDDg5eVFcHAwCkXJf9QlSofcwxNrWhrmhHhUwdXQRESS6SlDbk3AIljYcmUnXUM75DvvYE2Bh65BgwsG7BaL01JbloiCiM1u43TqOQYpHuVM6nkAMkyZuCnLXzkSBIHQKVORubrdNk1VaIArPu5qktINnLiYTLMIP2a+2B4Pl9L/IPh5aggPdsdms2M0V60ob73RgkwUEEQBux1uJGZJCutdgOjqg8vA9zGd2oJx589gs2CO3oLlchTaRyYjuvsX3kkpsdusGLbNB7sNee12Bfqt2i0mTIfWYDqyDmxWkKtQtXoMRYP7Ee7yuAK73Y7uj/edSnhlIAuog/zRyWXap79/QB5L39Chw53vbTYbrVq14dSpk6xfv5YRI0Y6j5nNZl58cRTt2jkKz1SrFsKgQf3Zs2cXDz74EBERdVEolHh7e+dbwvbyys2RvWTJIk6fPsXnn8/Ok2P9ZhYtWkBQUDDvv/+R8wFNpVIxY8Y7hV5fdPRJWrVqk2dfYmICAAEBeStA2my2PKnd5CX4fbRYLLzwwki6dcv9fkyc+CZeXt588smXTr2pevVQXnxxGP/8s4GHHurrbFutWggTJzqKd7Rp0w6DwcDSpYsZPPiZO6brrFMnEp0ui8uXL1KrVu1iy10VKfEdw9vbm7p169K0aVNq1KghKauVjCLbl9eSloogl1N93ASavzAOi9yhoK2+8Ge+c3RmHeerKclSi2j0VjKPHC4X2dyVji+VyWrGTelKiKtjuf10SsXd6OVu7mC1Yrh8qcDjgiDQLMKRRP/gGcfNqyyU1Zy+Rz3amLcGN6eab8VVkyqM2auOMerzbRw5n8SzPevy6cgOtK5X/oqORNmhrNcVl2e/RlbNkd3Drk8na/kkjIfWFju1VHERRBmaB19DXqs16s7P5nsYtFw/SdaKKZgOrQGbFXmNZo6gqkYP3PXKag4CVbNka2mw2+15/peXLl1kwoSx9O37AJ07t6Zr17ZcuXKZq1cv5zlPFEVatsxVBENCqqNQKIiPjy/y2Hv27GLOnK955ZXXad685W3bRUefpH37jnlWEzp27FKkMZKSkvD0zFtEJtfrK+//c/z4MXTt2tb5utUFoKi0a5fXWHT06CE6deqSR29q2LAxgYFBHDlyKE/bzp275tnu0uU+DAYDFy7c+ffTw8MTcFzvvYIUZXGPoKoWQuaB/dh0Dr9VS0Y6hnPnaJik4riPEbPNgtVmRSbmLg1suLIFmyhwspaaVid1pG3filuL298kSkqXkHb8fn49dhx3hUjv2lzLvMHp5LO0DGha5uMVhFWv5+Kbr2MzGAj/fBYyN7d8bVpE+LHpwDWOnEvEYrUhl4nY7HZOXkrGbodGtXwK6LloaNVyLFYbWw9f53piFk8/WPDSaUXiqlFgx5EpoFVdh6JaGn9dicpBlKvR9h6LJeY0xoO/Y7txEtP+FZiPb0TZsj/Kel3LbWyZVzCa+1/Os89myMC451csZxzR4ILWE1WHp5CHtSj3SmoViSAIaB6eWOkuAY45LbvvbUJCPNWrO4pU6HRZjBkzCk9PT1555XUCAoJQqZR8+OF0TKa8161SqfIZruRyOSZT0fJQX7lymWnTJvHggw8xYMCd87wnJSXmUzrd3d2LZAE1mYwoFHmNEX7ZmXYSEuLzuDmMHv0Gw4a9QHT0KT755IMiXcetqNVqNJq8bmAZGRl4e+f/PfH29nEWO8rBy8u7wO2kpMQ7jpvj8mC8TdzG3YiksN4jqMMcKS3sZjM2m42sQ4eIWzifXpGRRPtasdgtHE86TRO/3Hy0h+MdjvPRtV3pkOqFS6PG+Z6uy4J2Qa34/fx6bHYbCbpkIr3q8M+VbZxKPlsu4xWETKNB7uOLJS0VU1wsmgIU1johnrhpFWTozJy5mkr9MG92HI1hwfpoQvxcaFjTu1SyxqfoWbLpDHY7dGocRM2g0lVfKy05BQRuJGYRn6Jjzh8nMZgsvD+87P24JMofeVAkst5vYjm3G8POn7Hr0zBuX4D5+EY0vcYgupb8getmTCf/xa5PR9n84Tzpp+x2O5azuzDu/gW7MRMQUNS/D1XrAQjKss9AUhUQBAEUZRfxXdlcuHCehIR4evXqA8Dx48eIj49j5szP86SAysrKBMpuNSYzM5MJE96gevVQxo6dUGh7Hx9fUlNT8uxLT08vkg+ru7sHmZkZefY1bdocQRDYt28PLVq0cu4PCXHEdeiyDUE5KJWO/7nZnDftYXp6ej6luaDfDDc3d1JSkvPtT05OypcR4dZ2Ods+Pr75L+4mMjIcim9OFdB7gXtjXUYC1U2VvMxxMahr1kQZUh1t9VBqeYYB8OOxhXnOSdA7ntBU/gHUeGc6Xt17lIvy6KZ0Rcz+qP158W9qe9ZEJshIMaaSoK+45YqQ18cS/tlXaGoXnGpNFAWa1s7rFtAi0g+FXORaQhYXYtILPK+oBPu68GDrUJ56IKJK+Im2jPTngxfaMuqxRrhqFFyMSScmSYfOUPLcsxKViyAIKOq0R9tvCkK2H6st5TpZv4zFsPvX0pVaBayxZzHuWozp4GosFw8499vS4tCv+xjDlh+wGzMRvULQPjIJdcen71ll9V7DaDTyxRcfo1Qq6du3X/Y+A0Aey+mxY0ec0fvFRS5X5LPM2mw23nlnEpmZGcyY8XGRArbr1q3Prl078nyet2/fUiQZQkNr5JM/MDCILl26sXLl8iIVT8hJp3n5cm7blJRkzp8vWu75xo2bsm3bljwK9okTx4mNjaFJk2Z52m7btiXP9tatm1Gr1YX6peZcY/Xqd3dg481IFtZ7BLnWBVGrxabTYUnPwCWyLmHTHHnmws6t50zKOWzYOBR3hGYBTbienluOta53baeiarxxHWVAIEIZRxXKRTkmm4mLaZdRyZTU8qjB2dQLnE45h7/2zk+KZSaDpyd2mw3j9WsFZgoAh4K6/WgMh84kMLhHBC5qBa3q+rPreCzbDt8gPLh0T6uP3+e4ydjtdjL15lJlHygtrhqFc3ytWoG3u4rkdCPXErKIqO5ZaXJJlB6ZZxCugz7CeGQ9pv0rwGbFfOwvzOd2oXlgNPKA4gdh2HSp6Dd+7fBHrdUKec1W2K0WTEfXY4r6A6xmkClQNn8EZZOeCKL081JVsdlsHD9+DAC9XseFC+f4449V3LhxnYkTpxIU5IgzaNCgERqNls8+m8lTTz1LQkI88+Z9j59fyayrYWFhHDx4gP379+Dm5k5QUDB//LGK3bt3MnLka8TFxREXl5v+LyIiskAFdsiQZxk+/BkmTRrHww/3JzY2hl9//RmFQlFoloxGjZrw778b8+0fO3YCr776Ii++OJRHH32cJk2aoVQqSUhI4K+/1iKKIiqVGnAEptWv35B5837AxcUVUZTx888LcHEpmiHi6aeH8dJLwxg7djQDBz5Benoac+bMJiysFt27P5Cn7fXr15gx4x26d3+AM2eiWbz4Jx5//Ik7BlwBnDp1krCwmnh6ehZJprsB6Y5yD6GqFoL+7BmsqakAWLOyMF65TC+vpmxgMwC/nF5Fs4AmbLyy2XneIzUfAuD67K/IOhRF8KhXcW3aLF//pcFX482NrFhSjWkARHrVcSisyWfpVK1ilqDtFgsXxo/FmppK2AcfoSzgpluvhjdqpYzUTBMXY9IJD/agc5Ngdh2PZe+pOAZ1r1PqBPuxyToWrDuFyWJjyjMtK9Wv73piFmevphIW5EaIn2u2wpopKaz3CKomvVBEdkb/9xfY4s6CPh3979ORR3RC3XlokYOf7FYL+o1fY9enIXpVQ93lOWxx5zBs/wlbyjUAZNUaoO70TIVkKJAoHUajkRdfHOrww9VoCQwMpEWLVsyY8Qk1aoQ523l7+/Deex8ye/YXjB+fu2S/ePFPJRr3hRdG8umnHzJp0lvodFlMnDiVK1ccwVuzZ3+Rr/3y5X84leebiYioy7vvfsB3333NpElvUrNmOBMnTmP06BGFKo1du3Zn0aL5XL16xemrC+Dp6cm3385j+fJf2Lz5H5YtW4LNZsPfP5DmzVswf/6SPMv1U6dOZ+bM6cyY8Q4+Pr4MH/4Sf/+9Lp/7QEHUrVuPzz+fzZw5XzNlyluoVGratevAyJGv5isq8MILL3Po0EGmTBmPKIr07z+QF14YeZuec9mzZxddu3YvtN3dhGCXoiyKREpKFhZL1UpJdCux834gfddOfPo9ik+fh4lbOJ+0bVvx6tWb2UEXSDA4lt8/7fwuM/Z9TpIhBZWo5LOu0wFIWP4rKX//hUvjJlQb/Xqh48nlIl5eLkWam2WnV7H1uiOJ9OxuH3Eh7TKfHpyNi1zLh53eRqygUoxXZ85Af/YM/k8/i+ct0Zc5fPf7cfadiqdXm1AG3lcbu93O5B/3EpOkY8iDkdzX7M41zgubl/QsE299txub3c6UZ1oS4ld57gEL1p9i25EYerergc1uZ/2eK3RtVq3cgsKK85n5r1Hec2O+FIVh8/dgdizzFicXqmHHQswn/wWlBm2ftzBHb8N8cjNgR1C7oWr3BPLa7crt4auyPzdms4mkpBh8fILyBexUNnK5KH2XgP379/L66yOZNWsOzZq1AG4/N8OGPUWnTl3ypOy6lzh37izPPfcUv/yykuDggn+vKupzU9h3x9vbBZmsaL//RTIVTZhQuBN0DoIgMGPGjCK3lyg7hGw/o6xjR/Dp8zCqGjWR+55AVKkY2fR5pu2ZCcC840tIMjgc1ut45j4xenTqQsrff2FJTy/znKztg9s6FdbjCaeo5xOBWqYiy6LjWuYNQt0qpgygtl599GfPoDt58rYKa/MIP/adiifqTAIDuoZnV76qxq//nGXb4RuFKqyF4e6iZMTDDagR6IaXW+UGbNQIdIcjMVyOzaBdw0AAriVkVqpMEuWDIqw5sme+xnRgNeaT/2BLuIhu5TTEoAg03UciagteYjSf3u5QVhFQ1O+G/q8vsOtSAZBHdETddhCCuvJ9siX+W3zyyYe0bNkKd3cPLl68wE8/zSUiIjKfD2hBDB36PB9//AFPPvl0mZZJrSosW7aEBx986LbK6t1KkTSSvXv35tnOyMggIyMDuVyOp6cnqampWCwW3NzcCvWrkChPHNYNU4zDP9Wjcxc8u3R1HpULMix2KyeTTzv3NQvILYmoDAwi7L0ZKAtYgiktIW5Bzvf/Xt1OQ796/C+yP95qL4JdAst8vNuhrVefpD9Wo4s+id1mK3BJtFEtH+QygbgUPTcSs6jm50r7hoGs2HKOy3EZXIpNJyywdJ/zpnUcfrsJqXqS0w1EhnoVckb5EJadKeBSbAYD73ME7l1PyKyw7A0SFYsoylG3HoCy4f0Ydy3BcmEftpjTZC1+DWXzR1C1eCRPe7sxC8PuJQAIHv6YD/+Z/T4AdadnkQfXq/BrkJAAyMzM4PPPPyYtLRVXV1fatGnHyJGvFanSW6dOXbl69SpxcbF50ljdC9hsNkJCqtOzZ+/KFqXMKZLC+u+//zrfHz16lFdeeYWpU6fSq1cvZDIZVquVdevW8fHHH/P555+Xm7ASd0aV7Y9jMziW/ARBwGY2Ybx6DWVgAB2C27L1+k5nPlQRkbZBefOu3qyslrXSopFp0Fv1zlyfrQObl1nfRUVdsxaCSo0tMxPjtauoC7hZaVRy6od5c/R8EgfPJFDNzxVXjYJuzUNQK2V4upbNE/mpS8l8tuwI7i5KPhzRFoW84svnhfi5IBMFMvVmlHIZMlFAb7SSlG6oEiVkJcoHUeuJ5v6XMR4MdgRM2W2YDq7CHL0Vdc/XkPtk+/YpNCgiOmE+sQl7WhyIMpRNe6Ns2gehjMuCSkgUh2nT3i/V+U8+OaSMJKlaiKLI008Pq2wxyoViOw7OnDmTYcOG0adPH2d9WplMRt++fRk2bJjkDlCJqHNSW9lsTqX16swPuDrjXXSnTvJ4ZF7rSZBrwK1dAJC+dzeXp7+DLjuKtKwI93Qoh3F6R8ooo9XE4lMreG/PJ5itFZNKSZDL0UY6/DN1p25ftaR5hCORdFR2eiuAQd3r0K9TrTJTWGuHeODuoiTYR0umvnyrEt0OhVxGcHb1rWsJWQT6aJ3vJe59VC364TL4c0TfMADsWcnof3sb/b9zsMRfQLf6XczHN4DdhiygDtrH3kXV8lFJWZWQkKhwiq2wnjhxgoiIiAKPRUREEB0dXWqhJEqG8qZUTfoL5wFQVa+OzNUNm96hwLorcxPm13QreCnEcPEixksXSb0l/1tpqebicAtIMznymSpFBSeSThGri+dC2uU7nVqmaOs6iifoTp64bZumdXwRBLgSl0liqr5c5FDIZUx9thVvDGpWqb6sESGehFdzRyYTnAFg1yU/1v8MotYDl0enob7vBchWRC3ndqNf/S62xEug1KDq9Cyahycg87q3fOIkJCTuHoqtsLq6urJr164Cj+3atQtXV8n5vrIQRdEZKGXITn7s/8RT1Pr8Kzw6dgJgWIPBzvZN/RsU2I9HZ0dN5qwjh7Fkp8gqCxr41nW+P5l0GkEQ6F+7Dy83GUaYR+gdzixbtPUdCqv+7Bls5oItu+5aJREhngBEnc0tgZeuM7F8yzm+XH6kTGRxd1Fitlj5a+8V/t53pUz6LC6DH4hg0pCWNK3tS7sGAQzqVpsm4RWTG1ei6qCo0x6Xp79GViM3aEUWXB+Xxz9AWa9rnqpWEhISEhVNscPAH374YebOnYvFYqFv3774+vqSmJjImjVr+Omnn3j22WfLQUyJoiJqtFgz0jFdc+RGFJVK7DYbptgYFIFB1PGqxWO1+2C2WajnU3DqIlVwNdS162A4d5a0ndvx6d23TGQL96xJTtXri2mXqe8TSavAss33WhSU1UKQubljzUjHcOE82si6BbZrHuHH6aupRJ2O54FW1Z37N+y7itVm50pcBqEB+Uu8Fpej55NZtvkcKqWMdg0DcddW3nJr43BfGocX3k7i3kSUK9E++CrW5KvYUuNQ1GpZ+EkSEhISFUCxFdYxY8aQnJzM/PnzWbBggXO/3W7n4YcfZsyYMWUpn0QxkXl6OhTWeEe1ELvVyvnXR2PTZVFz5qcofHzoFtq50H48O3cl9txZ0rdvw7tX7yInGC8ML5UnycZUZ1otq83KqnN/cib1PK81G4FWUf5lHAVBQFu/Phn79mK8fu2OCusv/5zl7LU00rNMuLsocdcqaR7hx/7oeLYeucGQB0qfr7R5hC/NI/xoEu6Di7ria3nY7XaW/nuO8zfSGN6nPofOJnItIZNnetZFXsT8eBL3FjLv6si8qxfeUEJCQqKCKPavo1wu58MPP+SFF15gz549pKWl4enpSevWrQkPl0wzlY0qOBjT1StgswIgyGQofLwxWcyYE+JR+PgUqR/Xlq0Qf12MOTEBw6VLaGrVKvykItDQpx7bbuzmQtolAGSijJPJZ4jTxXMm9QJN/RqWyTiF4fvoAPyfeArZHVxYfDzU1Ah043JsBofPJdK5iSODQpemweyPjmfPiVge71oblbJ00f2CIDDq0UaAQ3k0mqyl7rO445+8lMy1hCyuxWfyx85L6I0WHmwVSoi/5OIjISEhIVH5lNicU6tWLWqVkRIjUXa4tWpDxt495ORkBaj22hvI3NyLZSUVlUoChz6PMigYZWDZ5UnNsaAm6JOc+yK9ahOni+d08tkKU1gVPg4fTasuC0GhQLxN9ZrmEX5cjs3g4OkEp8Jat4YXfp5qElIN7IuOo1PjsslbezEmnZ83nKaaryvDeldsfssagW5cS8jiclwm3VtUQy6KaCvB2ishISEhIVEQJVrvM5lM/Prrr4wZM4Zhw4Zx6dIlADZt2sTVq1fLUj6JYqLwc9TxNifmpmOSe3iCIGDNLF7kt2uz5mWqrAI08c0N9Lqafh2Aut61ATidcq5MxyqMmO+/5fyro9AdP37bNjnprU5dTkZvdKSeEgXBqbxuO3KjzOSx2e1cjMng4JkEdIaKSfOVQ/sGgTz1QARt6gfwaOdwHu5YE293dYXKICEhUf7MnTuHHj06ObczMjKYO3cOFy9eqBR5li1bwu7dO/LtHzXqBcaNe63C5OjYsaXzdd997XjkkZ6MGfMKa9euxmIpv7SDZ8+eZu7cORiyU1EWlaioA3Ts2JLo6NunZ7zXKLbCmpyczGOPPca0adPYt28fu3fvJivLkbPxn3/+Ye7cuWUupETRUfg6LIc2nQ5zisNP1BQbw4Uxo7k0ZaIzaX9RsaSnk/zXOtJ2bC8T+UI9clNvbc8u1VrHMxwBgThdAimG1DIZpyiIWhew2zFevX10frCPlkBvLRarnaPnc63CHRsFIRMFzl9PL7NSpuHBHjzbqy4fvNAWrVpRJn0WlXph3nRrHkKwrwupmUa2Hr7O5kPXK1QGCQmJiiczM4P583/g0qXKUlh/Yffunfn2v/HGeEaNeq1CZRkw4H989918vvjiW0aPfgNfX18+/vgDXn75eXS68slNffbsGebP/6HYCmtkZF2++24+NWrULBe5qiLFVlg//vhj0tPT+e2339iyZUseBahNmzbs37+/TAWUKB6iSgXZ1an00acAkHv7YM3KwpqViTU9vVj9ZR09TOKKZSSvW4vdZisTGWWCwz/zWKLjyVCr0FDD3RHgEV2BVlbvXg9R86PP8Hm4323bCILgtLIevKmIgIeriqa1HQ8HB08nFHhuSejcJBh3FyUxSVncSKzY5P12u52EVD3XE7L46a/T/Ln7UoWOLyEhcfdjt9sxmUyl7qdmzVqEhoaVXqBi4O8fSMOGjWjSpCndu/dg4sSpzJz5OdHRJ5k1q2pV8XRxcaVhw0ZoNP+dioTFVli3bNnC6NGjadCgQb6ynQEBAcTGxpaZcBIlQ1A5ktAbrjiS8YtKJTWmvEPtr79D7uFRrL7cWrVBVKsxx8ehP102RSHUMod8GeZchSzSK9stIPlsmYxRFBQ+vii8vbGZTNjucIPNUViPXUjCbLE69/ftEMZbTzbj4Q5hZSrXjqMxTPlxH4s3ninTfgvjg5+jeOu73WTqHe4IyelGsirYNUFCQqLiiIm5wcCBDwMwZcp455J4TIzD1clkMjFnzmwee6wP993XjsGDB7Bhw195+nj//WkMGfI4u3fv4JlnnuC++9qxY8c29Ho9n302kyeeeJTu3TswYEBfPv54Bpk3uaYNGNCX2NgYVq5c7hx73bo1QF6XgNzl71N5xrZarfTt+wDffPOlc9+lSxcZP34MDz7Yha5d2/Pmm69y/fq1Es9R27bt6dKlG3/99afTypqYmMiMGe8wcOAjdOvWgUGD+jNnzux8inrHji1ZvPgn5s6dQ9++D9C7d3dmzHgHvd5RjGbdujXMmPEOAH363E/Hji0ZMKCvc25udlPIeb3//rRb5iTXJSAzM5N3351Cjx6d6dPnfr755ksWLVpAx473Rnq6YkdVZGZmEhxccJCJxWLBarUWeEyi4pC5uGIxGDDF5PpXqqo7LJh2qxVBVvQIdFGlwrPHg2C3oQgMKhP5annW4FjiKezkWufretfm78v/cjrlHHa7Pd/DUHkRt3gR6du3EvDMUNzbdSiwTViQG15uKlIyjJy4lOK0rJZFDtaCqBvqiSiCSiHDaLaiUlRMxgB/Lw3nrqcRm6zD211FcrqR6wlZRFT3rJDxJSTuNux2OyZb5T3UKcXSuQ75+Pjy/vsfM2nSm4wYMZJmzVo69wO8/fZ4jh49wtChwwkLC2P37p28994U3NzcaHfT/TIxMZEvv/yUZ555Dn//APz9AzAYDNhsNl544WU8Pb2Ij49j4cJ5TJw4lq+++g6AGTM+5s03X6VRo6YMGvQUANVuqtiYQ9OmzfHz82fTpr+pWzc3IDUqaj8pKcncf/+DAFy/fo0XXxxGrVrhTJw4DYVCxvz5P/Lqqy+xZMlvKJUly3HdunVbNm/exOnT0TRr1oK0tFTc3T145ZXXcXNz4+rVK8yb9z1JSYlMnDg1z7m//baMJk2aMWnSNK5cucy3336Fl5c3L730Cu3adeSZZ57jp5/m8umns3BxcUWpVDjnxmTK/WydP3+WTz75gNDQgitUOs55h6io/bz88mgCAwP5/feVnDlzukTXXBUptsIaEhLC4cOHadeuXb5jR48epWbN/44/RVVF7u2NJSkRS1Juhaas40eJX7wIZVAw1Ua/Xqz+fB/pX6byPVijO8cSHU/K1zJuEOIWTE33GihEBemmDGKy4gh2Ldtgr9shqtXYLRZ0J0/eVmEVBYHmdfz4J+oaUWcSnArrzcQm6wj0Lpscsr6eGma80BZfj4pd6qkR6Mau47Fcjs0gxM+V5HQj1xIyJYVVQqIA7HY7n0V9U6FlpW+llkcY41qPLPH5SqWSiAhHLumQkOo0bNjIeSwq6gA7dmzjs8++pnXrtgC0atWWhIQE5s2bk0dhzchI59NPv6J+/bxZXsaOneB8b7FYCAoK5uWXn+fKlcuEhtYgIqIuCoUSb2/vPGPfiiiKdOvWg3//3cjIka86DRobN/7t7Adg/vwfcHNz5/PPZ6NSqZDLRerVa8Tjjz/M2rW/8+ijA0s0T/7+AQAkJzviGMLDa+fxr23UqAlqtYb335/KmDFvoVbnBqz6+Pgwdep0wGGtjY4+yZYt//DSS6/g5eXlVNAjI+vh6enpPC/nmgBSU1N5551JtGrVlsGDnylQxosXL7Bt22YmT36Hnj17A9C6dTueeOLREl1zVaTYLgF9+/blhx9+YNOmTU7/VUEQOHr0KAsXLuSRRx4pcyEliocywPHlstzkrypqtJgTEjBcvlTifs0pKejPl97HtOZNZVi3X98DgEKmoLan42GnIrMFuNR3ZC3QRZ+8Y0Ba8wiHknr4bCLWm3x5LVYb7y88wMTv95Spz6mvhwaDycKaXZc4fFNp2PIkLNBhMb4Um041PxcAriVUrB+thMTdRcWsBFUG+/btwd3dg+bNW2KxWJyvFi1acebM6TyrqZ6envmUVYC//vqToUOfpEePTnTt2paXX34egKt3CHS9HT16PEh8fBxHjx4GwGw2s23bFnr06Olss3//Hjp16oxMJnPK6+bmRu3adUoVTZ/72yA4t5ctW8JTTw2kW7cOdO3alnffnYzVauXGjbzuB61atc2zHRZWk4SE+CKPbbFYmDx5HKIoMm3a+4i3SU+Zc30dO3Zx7pPJZLRv36nA9ncjxbawDh8+nKioKEaNGoVHtj/kc889R2pqKp06deLpp58ucyElioequkMhtOkNefZVG/Mm6jssJ9yJrONHuf7l5ygCAgh774NSL9mrZSoMViOxutwvbqdqbWnoW49GPhWXg1RduzaCQoElJQVzbAzKoILdXSJCPXFRy8nUmzl7NY26NbwAkMtE3LJLqW47coNB3euUmWwbD1xj1bYLBPloaRTujayMqo3djur+rghAaqYJHzeHhaCsMiBISNxrCILAmOYvVbpLgONeXLzsL0UhLS2V9PQ0unZtW+DxpKREp+XR09M73/GtWzczffpUHn64Py+88DLu7p7ZS+ZjMZmMxZanbt36hISEsnHj3zRp0ow9e3aSmZnhdAcAhyVy2bJfWLbsl3znK5UlT9OXo2D6ZBfeWbZsCbNnf8mTTz5N8+YtcXNz49Spk3z22cx8fqyurnldx+RyRbGC0r744hNOn45mzpz5uLu737ZdYmIicrkc11uK4Xh5eRV5rKpOsRVWhULBDz/8wLp169iyZQtJSUl4eXnRtWtXevfufVvtX6LiUNfMLuhgs2IzmRCVSkSl0mlNLAma2nUQlErMsbHoz55BG1G6kqT1vCM5lHA0j1WzSQUVDbgZUaFEU7sOulMnyTp18rYKq0wUaVrHl53HYok6k+BUWAE6Nw3m8LlEdh2P5bEu4cjlZfMd6N48hCPnErm/ZUiF+PSqlXICfbTEJOmQyxzjXU/IqlCfYgmJuwlBEFDJSuYXWdVxc3PH09OLTz75ssDjXl65SmpBt4fNmzdRp04E48ZNcu47dOhgqWTq0eNBVq1awWuvjWXTpg1ERtajevXcFTt3dw/atevgXPqXyUSsVseKmFZbcpetvXt3o1QqiYx0GFM2b/6HDh068+KLo5xtLl26WOL+b8fq1b/x+++/MX36TGrVunMlUV9fXywWC5mZmXmU1pTs9Jb3AiUqZSMIAr1796Z3795lLY9EGaC6yYpqvHIJTe0IANJ2bCP1n424tmiFT5+Hi9WnqNbg3qYtadu2krZ1S6kV1jqeNTmUcJRL6Xn9v3bHHOBowgkeDLuPMPfQ25xdtmjr1Ud36iS6kyfw6nb/bds1j/BzKKxnE3ji/jpOJa5RLW9nUFbUmQQ6NC6b4DStWs7kpx1BEDa7HYvVhlxWvg+Eox5thKerCoVcZNGGM+iNFpLTjfh4SEUEJCTuRRQKR5DPrVa/Vq1as2TJQuRyBbVrF3/lyGg0IpfnDQq7NcMAFM/ieP/9DzJ//g/s3LmdXbu289xzI/Icb9myNRcvnqdOnUhkMhlyuYjFUrp0jHv27GLbts307dvPmULKaDQ45y2HDRvWl6j/nDm61ep85MghvvjiY55+ehhdunQrtJ+6desDsH37Fnr16gM4sijs3Fk2OdSrAsVWWEePHs1jjz1Gp06dJGtqFUWUy5H7+mJJTMRuzq3QYTMYMV69itwr//JNUfDo1IW0bVvJPLgf6xODkXvefnmiMCI8HWmsrHYbl9IuE+bhULJPJEVzNPEE1d2CK05hrd8AVq5Afzr6jlkUGoR5o1LISE43cik2g5pBjuuXiSKdGgfxx85LbD18vcwU1hxOXkrm13/O0bFxEA+0ql6mfd9KkI+L832gj5brCVlcTciUFFYJiXsUb28fXF3d2LTpb4KCglEqlYSH16FVq7Z06NCJN954hcGDnyY8vA56vZ6LFy9w/fpVxo+fcsd+W7Vqw2efzWT+/B9o2LAxe/bs4uDBffnahYWFcfDgAfbv34ObmztBQcF4eHgW2GeNGmFERETy+ecfYTAY6N79gTzHn3tuBM8//zRjxrzCww/3x8/Pl4SEBA4diqJJk6Z5/F0LIj4+luPHj2GzWUlKSmTPnl389def1K/fkJEjX8tzbcuX/8pvvy2levUabNiwnmvXSpY6KywsDICVK5fTqVNX1Go1gYGBTJo0jpCQUNq168Dx48ec7W8O1LqZmjVr0bnzfXz55ScYjQYCAoL4/fffsFot98wKWbEV1kOHDrFx40Z8fHzo378//fr1Izz8zqZqiYpHGRiEJTERc0ICZLuEujZpisLHG1UJK2Oowmqiqh6K8eoV0vfswq/nnb/8dyLILcD5fuPlLQxv7Ih8bBvYglDXajTyq1/ivouLKrQGolaLTafDcOkimvDaBbZTKmQ0quXNgdMJRJ1JcCqsAJ0aB7Nm5yWir6QSm6zDy8ulwD5KQmKagWsJmfwbdY37W4YgluPNx2yxcuJiCjHJWdQIcMNms2O1lr1/nISERNVAFEUmTHibH374htdeexmTycTy5X8QFBTM9Okf8fPPC1i5cgVxcTG4uLhSq1Y4Dz3Ut9B+H3nkUW7cuM5vvy3jl19+pnXrtkyd+j4jRjybp90LL4zk008/ZNKkt9Dpspg4ceod+7///gf55puvnKmubiYkpDo//PATP/zwLZ999iF6vR4fH1+aNGlGeHjhVuIVK5ayYsVS5HI5Hh4ehIdH8OabE+nZszdyea669Oyzw0lNTeXHH+cA0LVrd157bSxvvVW8DDzgyAYwbNgLrF37O0uWLMTfP4BZs+aQmppCamoKL744LE/7Xr36MGnStAL7mjDhbT7//CNmz/4SpVJJz559CAurxerVvxVbrqqIYC9mrU6bzcb27dtZtWoV//77L2azmSZNmvDYY4/Rq1evfA6/9wopKVmlXlqoSOIWLyRt8794P9QH30cHlFm/qZv/IeWfjfj0fhjvTh3x8nIp8dy8unkiFruF2h41eb3FS2UmY0m48c0sMqMO4tPv0Tu6S+w5Ecv3a04S5KPl/eF5gxG+WH6Eo+eT6N2uBi8OaFpmnxmrzcZfe6/QpWk1XDXlW7JVb7Qw6vNt2IHPR3XAw1VVpv3L5WKpPjP3MtLc3J7Knhuz2URSUgw+PkEoFFXLZ7Uslr3vVaS5gZdeeg65XM6sWXPy7K+ouSnsu+Pt7YKsiK5uxV7TF0WRLl268MUXX7Bjxw4mT56M2WxmypQpdOrUibfeequ4XRaZ5cuX8/DDD9OoUSPatWvHiy++mOf41q1b6devH40aNaJHjx4sXry43GSp6tiMDn+YjH178+xPXr+OKx++T9bJEyXq16NzV8Le+wD3du1LLWO4Z5hDJmNqnv2HE44z/8QSzlRgeittPUdAmv7snatLNQ73RSYKxCTpiEnKm/Kpc5Ng1EoZMrFsLaAyUaR3uzBcNQquxmeSoSt92cPboVHJCcjOJ3slPhO90cLl2IxyG09CQkJComzYsuUfli5dzIED+9ixYytTp07g2LEjDBz4RGWLViaUKOgqB3d3dwYPHszgwYM5cOAAY8eO5Y8//mDmzJllJZ+TWbNmsWDBAl588UWaNGlCWloa27fnOhMfOnSIl19+mUceeYTx48cTFRXF9OnTUSqVDBxYsmTBdzNyd0fKMUtGep79xutXMZw7i+H8uRJlDbjZv9OSng6lWPqu4V6d0ynnSDbkjWI8kRjNgbjDuCvdiPAqeHm+rHFt3gJltWpoConE1Krl1Avz4viFZKLOJNC7Xe71N6ntw2ejOuCqLR8LzB87L/L79ov0aFW9TNNn3UrjcB+CfLQYzVZGfr4NmSjw7Rtdyj3gS0JCQkKi5Gg0Wv7+ex1Xr17FYjETGhrG22+/R+fOXStbtDKhVAorwM6dO1m5ciWbNm3CaDTSrFmzspArD+fPn+fbb7/9P3vnHR5F9TXgd7an95Ce0BISeu9dQASk2hsKKooUsSs2FCyoCCKgomL9LBT9gYCgIr13CCEhkIT0tqnby/fHJoGYtumUeZ8nD+TOvXfO3OzOnDn3FD7//HMGDBhQ1j5ixIiy/3/66adERUWxaNEiAPr06UNaWhpLly5l8uTJN12AmCo0DACrvrw1zm3gYJzad8ChbXid5zYXF5P66TJ0CZfw+Hp1nedp6XIlqCqpIJkQV5sjeTvPNuxLO9SkBQRkbm7ISvIKW00mBFnVX41u4T5XKaxhZe1SiQSpovE+Z60CXLECRVpjo6aaKlWGrVYrDkoZKoWUvEI93u5NW3lLRERERMR+evfuS+/eFauQ3ijU6emalJTExx9/zJAhQ5g+fTqHDx/mwQcfZOvWrfzf/1VM2Ftf1q9fT3BwcDll9WoMBgMHDhyokGZr3LhxZGVlER1d9woX1yuqssAhK8bc3LJ2x4h2uPbtj+7iRbJ/31DWnrPxd7I3rMNcZEsUn7dzB9kb1qFPTQWg8NhRsjesQ3M+BomjI6bcXKwGAym//6/OMnbyvWLh3ZW8v+z/pVbVlKI0Cg1Nl7g+f+8eLr34HNkbqndQ79rWBwG4lFZIboGuwvFCjYEN/14gS61tUPnah3my8NHeTB8b1SRRn4Ig8OHMfnw4s7+orIqIiIiINCu1trDef//9HD16FJlMxtChQ5skxdXJkycJDw/n008/5fvvv6ewsJAuXbrwyiuvEBkZSVJSEkajkVatWpUb16aNTfGJj4+nQ4f6JaW31yn4WkHm623L5my1YkiIx8HXVlrUarWS/b/fKTp7Bm18PH6TJwOg/nMLFp0Oz8GDkMlcKdy3B218PE5tWiMLCUJ7+iR5u3chc1Dh2j4KZXAQxuws0rdsxWPchLrLKcgwWU0kFl4uS7jvIXMlyCWA5MJULuTH09O/4a32lcqikGHMzkIbG1Nt8n8vNxVtgtyIS87nRHw2I3uWT7/1xbpoTsRlc8fQNozrH9agMga3cEGjM7H5QCJ9O/gR6N1w2QhKsVisrPrtDBfTCnhtak8QQKMz4epUf1eH0u/R9fZ9agrEtama5l4bi+XaTAtU+t5acqsXuQpxbaqmOdZGKhXqXVSn1gprcXExL7/8MuPGjcPd3b1eJ7eXrKwszp49S1xcHG+++SZyuZzly5fz8MMPs23bNvLz8wEqlC0r/b30eH1wdb3+LEwShcIWfJWWUi7NkjWiDTKjDo924WXt/qNHYTEa8fT3Ru7qhGbwQPSREXi1CsHJwwlTr244uDnj2TESdw8n9P37YslT0/KRqfVaG09HNzKLc1Ab8srJ2CUgiuTzqVwsTmCkR+WW9YbGeWAfXH09cY2KQuZY/TUN6hZEXHI+p+JzuWtk+VKyfTsFcCIum5ikPB4c2/AK5Vc/HuXfo8lkF+h46aFeDT4/2AKuMtVa/j2Zxm87L9Al3JfXp1deorEuXI/fp6ZCXJuqaa610emkZGdLGuSh2xiILzlVI65N1TTF2lgsAhKJBDc3R1Sq+uXzrrXCumHDhpo7NTBWqxWNRsMnn3xC27Y2/7r27dszfPhwfv75Z7p16wZQ5TZpQ2yfFhRoy0q8XS9InJyw6PXkX0xArb4S0S5p1wGPdjaLc2m723ibpbXIDKiLcRw0DEfAABjUxcg6dsOjYzesJWOUPfrQunc/XF0d6rU2oS7BZBbnoDXqysnY0ikMgJOp0eTmFjVR4mMJQut2FOotWLWFCNXsGkQFuwNwOj6bpBQ1LlcFWrXxt9WOPpeQQ3pmAUp55YUI6srIHkFcSFLTM8Kn3Jo1JCG+zqRmF5OdW4zJbOViSl6DnEsqldT7M3OjIq5N1TT32hgMeiwWC2az9ZpKkyQIV8qPilbE8ohrUzVNuTZmsxWLxUJ+vgat1lzhuKurg92Kc72DrpoCNzc3vL29y5RVAF9fX1q1asWFCxcYOnQoUNGSWlBgi5D/r+W1LpjNlmvqRmUPMg9PTLm5GLKzGkV2Q1YmSYu/oSghkbCF7yF1qL31o49fLw6nnwAgT1OIs8JmkWzpEoZUkJKjU5NemI2Po1dDil4lRcePkv3bBhzatKHFA1Or7OfhoiTY15nLmUUciclkYKeAsmPebiq83R3IztNyLiGXDi0bVnY/D0fefKQXgiBgMJiRNHAaLYCQFi4ciM5AXWhLj5ZboKegSI+jqmHywF6P36emQlybqmmutblWi2eUKhuiQlYRcW2qpjnWpiFe9uxSWIcNG2a3hUsQBP766696CfVfWrduTWpJ8M/VWK1WJBIJISEhyOVyLl68yKBBg8qOX7hwoWz8zYhD23B08RcQFA2b/L0UqxXyT9lKxuXv+hfPUaNrPUc7zzY4S50oMhcTn5dA55JALKVUQUu3EC7kXSJGHddkCitSKYaUZKz/qetcGd3DfbicWcTx2OxyCqsgCHRp68Nfh5OITlA3uMJaeo6j57NYtzOe+0eGExVWt3K7VRHqZ7MSp2QX4+mqJLdAT3JWMeEllmUREREREZGmxC47bK9evez+6dmzZ4MLOWTIELKzs4mNvZLUPSMjg4sXLxIREYFCoaBPnz5s2bKl3LhNmzbh4+NDVFTTlfm8lnBqb9v2t2g1jTK/0tcXt86dACg8sL+G3tVQ8incmbKvXHM7D5tFvSnTWzmGR4BUijEry1bWthq6hfsAcOZSLlq9qdyxziXHohNyK4xrKGKS1KTnath6KKnB5w5tYVNYs/N1+JUUEkjJarqMDSIiIiIiIldjl4X13XffbWw5qmXEiBG0b9+eWbNmMWfOHBQKBZ9++imenp7ceeedAMycOZP777+f+fPnM27cOI4dO8avv/7KggULbrocrKXIfWxKkyk7G6vFUq1PZl2JePZpDj/8KPrLSegSElCFhdV6Dolgk+uCOr5ce3vvdqj1eXT0broXDonKAVXLVuguxKE5F42bz+Aq+wb6OOHr7kBmnpYzl3Lp2e5KXevObWxZGS5n2CpTuTRCMYGx/cJwcZAzomdwg8/tqJJxx9DW+Lo7EJecT3SCmstZjeMvKyIi0nR8+eVnfP31F3h7+7B+/R8Vno/PPjubAwf20a/fAN5//2OOHTvC7NkzWL36W9q1s92Lp0wZR79+A5g374WyOX/66Xu2b99d4Xz1YeHCN9iyZVO1fbp06cby5Z/X6zxpaancccftvPXWuwwdeku95rKXAQN6VHu8Ia7LXjZv3siiRW+yadNfZcH0Awb04Mkn53DvvQ80iQz2cF34sEqlUr744gsWLVrEa6+9hslkomfPnnz44Yc4OtqsP127dmXFihV89NFH/Pbbb/j5+TF//vybsspVKTIPTxAErCYT+uRkVCEhNQ+qJVIHBxQtWqBPSSFvx9/4PTyt1nN4O3hRYCjETHn/lhCXIO5tN6WhRLUbx8ioEoX1LG6DqlZYBUGgW4QPWw8mcSw2q5zC6uGqom2QG04qORq9qVEUVjcnBbcPaAlAYnohQb5OSBvwpWR071AAjCV+R8mihVVE5IZAJpORn5/H8eNH6d79yq5oXl4ehw8fxMHBsawtIqIdq1Z9TWhoyyaXc+rU6YwvCQgG+Oab1SQmJvDaa2+XtTk5NXwmlqZg1aqvK23ftWsHP/74Lf36NU12nKpYtepr/Pz8m1WG/1InhTUvL481a9Zw4MAB1Go1Hh4e9OvXj4ceegi3kmpBDY2XlxcffvhhtX0GDx7M4MFVKxg3G4JUCoIErGa0cecbRWEVZDJMxTbLW+GhA/je9wASRe2Us5HBQ1iVvwaAbG0u3g5X/DFTitI4nnmKFo6+9PRrmnysTlHtyd34O5pz52q0THcLtymsJy9kYzRZkF+V8mb+Qz2aJFhjzZYYdp1M5eHb2pXzpW0I9EYzKqXtNpGSVdyoFbZERESaBrlcTo8evdi+fWs5hfWff7bj7e2Dv/+V+4iTkzMdOnRsErnMZjNWqxVZSaXBwMAgAgODyo67u3uQnp7WZPI0BHq9DqWyYjqnyq4hPT2d//1vAz179uaee5rXsnktrnGtzTEZGRlMmjSJVatWUVhYSEBAAIWFhaxYsYKJEyeSkZHRGHKK1BGJg+2Lor/c8H6OYLMy+k65E+duPQh67sVaK6sAHX2vbPkfyThZ7lisOp4tCX9zIO1IvWW1F1XLVghKFeaiQvTJl6vt2yrAFTdnBTqDmXOJ6nLHmkqx8/N0RAAychu2staF5Hye/GgnP2w7j1QioNWbyC2oORhNRORmwWq1YtHrm+3HWo8w71tuuZV///0Ho9FY1rZ9+1aGDx9Zrt+xY0cYMKAHMTG1qxhZWFjIBx+8y/jxoxg6tC+PPHI/hw4dKNfnqace4/nn57JlyybuuWcSw4b1Iy7uvN3n2Lx5IwMG9CAvL69c+wMP3MnChW+Uaztz5hRPPz2TkSMHM2LEIB599CEOHy4vz9XExZ1n7NgRvP3265jNtnRM+/bt4dFHH2LYsP6MHXsLH3zwDlrtlftu6Vrt27eH+fOfZ+TIwbz66ot2XYvZbGbBgvnI5XLmz3+zwvNj8+aNPPTQ3Qwb1o8JE0bz2WefYjKZyh0fMKAH0dFnmDPnCYYP78/dd0/i4MH9WCwWvvhiJbffPoqxY0ewatVyLJbqI/YHDOjBjz9+V/Z76d/qn3/+4p57JjFixEBmz55BSkqyXdfXENTawvrRRx+h0+n45Zdf6NSpU1n7qVOneOKJJ1iyZEmz+7yKXEHm4oqhuBhDI75IeAwYgEuffvWaQyZIMVnNHM88wa1hQ8vaozzD6dGiC+292tVXTLsRZDIcIyIoPnUSzbloVCGhVfaVCAJd2/rw7/EUjsVm0al1+YwABRoDMYlqwoPdcXdunGwNw7oF0rGVJ4E+zg06r5+XI1Yr5BTo8fdyJC1HQ3JWEV5u9Uv+LCJyI2C1Wrn87kJ08U0XFPpfVG3a0vKV+XUaO2DAQN57z8KBA3sZOHAI6elpnDlzinnzXiA6+ky95DIajTz99Exyc3N49NEn8fHxZdu2zTz33By++uoHWpeVDoeYmHNkZKQzffoTuLi44Ovbol7nroxTp04wZ84TtG/fkRdemI+LiwsxMdFkZKRX2v/MmVM8++wcRoy4lXnznkcQBHbs+IvXX3+Z224bx7Rpj5OTk82qVcspLCzgzTffKTd+8eJFjBw5mkWLptgdQ7NmzWpOnz7J4sVL8fLyLnfsp5++Z+XKT7jzznt56qm5JCQk8PnnK7BYLDzxxKxyfRctepMJEyZz770P8v33a5g//wVuu20sxcXFvPLKG0RHn+HLLz+jbdu2DB8+qharCHFxsajV3zFjxiwsFjPLln3EggWv8tlnlbs3NDS1Vlh3797N3LlzyymrAJ06dWL27NksXbq0wYQTqT8yb28M6WmYchsvWh0gf9dO8nb9izIkBI/hI1EGBtZqvIvCBbU+j2xteStlCydfHm5/b0OKaheO7aLKFNaa0nV1D7cprCfisrCMiih3bPn601xIzuehWyMY3KV2a2IvCrmUQB9nCjUGth2+zG19QnFQ1t893dlBjrebikKNkWHdgghp4UyIr0sDSCwicoNwHbvHKJUqBg4czPbtfzJw4BC2b99KaGhL2rYNr/fc27ZtIS7uPGvW/B8tW9pKpvfu3ZekpCTWrFnNW29dMWoVFhawevW3jaKolrJy5TICA4NZunQlUqmtkEuvXpVX7jty5BAvvfQMkyffxYwZTwG2l5NPP13KsGEjePHFV8v6enp68vzzT/PQQ9Np1epK+swBAwZXUCSr4+TJE3z77Vfcddd99PmP8UejKebLLz/n3nsf5PHHZwLQs2cfpFIpn376Mffe+wBubu5l/adMuYsJE2yxHz4+Pjz44N2cOxfN55+vAWx/hz17dvHPP3/VWmEtKirkq69+wMPDo+T3It57720yMzMa9e9XSq2faoWFhQRWoYwEBQVRWFhYb6FEGg6Fvz+aM6cxFzduwIwuMQF9wiX0CZcQpDJa3Fc7/5tQ12DUWXnozRW3nLM0OZzIOo2zwpm+/tVHVjYUjiWp0LSx57EYjUjkVSfMjwhxx1Epo0Bj5EJKPlEtr/jgRoV6cCE5n3OJ6kZTWEv5+NeTXEorRCaVMH5AwwRIvHR/d9ycFI1SnEBE5HpGEASCX3gZq8HQfDIoFCVbx3VzDRg5cjQvv/wsGo2G7du3MnLkrQ0i16FDB2jdug3BwSHltq179OjFX3/9Wa5v69Ztyyk7V/cHyvxZ64pOp+Ps2TM8/vjMMmW1Kvbv38tff23joYce4aGHrgQQX76cSHp6GrNnP1NOvi5duiMIAufPnyunsPbt27/s/xaLpdz2u0QiKWd1LSgoYMGC+bRpE16mkF7N6dOn0Go1DB06vNy5u3fviV6v5+LFeLp27V7W3qNH77L/BweHlrSVL+EdHBxCcnLt3QTbtAkvU1YBwsJsz5nMzMxrU2ENCgri33//pX///hWO7dq1i6CgoEpGiTQXqpAwAKz6xvU9dBs4CEEqIe+fvyk8sA+fKXciUdq/BT4kqD8nsk5jxUqBrhBX1RVL3oX8S/wWv5lQ1+AmU1gVgUH43vcgDhHtEGq4YcqkEjq38WL/2QyOxWaVV1jDPPnf3gSiE9RYrFYkjWiRGdUrhM37E2kT2HCBjx4utr9hplrDup0XMZktzJrcqYZRIiI3B4IgINTiPnet0aNHLxwdnVizZjUXL8Zzyy21s7hVRX5+HrGx5xkypKIV879K49UKEFBhzJ499YtfKCwswGKx4O3tU2PfPXt2oVQqGTGivOJe6iP78svPVjruv64FV1/T119/wddff1H2+8MPP8q0aY+X/f7++wspKChg6dKVyCsxjOTn2879yCP3V3ruzMzy7n7OzleenaXzXd1W2m6ow4uWi0vFecBWurgpqLXCOmnSJD788EOsVisTJkzAx8eHrKws/ve///H999/zzDPPNIacInVE1aaknK3ViqmwEJlL42zpqsJaogwJRZeYiGNEO6xmE2D/jby1W1jZ/3ck72Z8m9vKfm/nYfN3SipIRmPU4iivfQnY2iIIAu5Dh9ndv1u4b5nCet/IK1tqrQJcUSqkFGmNJGcWEdKi8bbUe7TzpUc7XySC0GDR/Fq9icMxmVzOLOJwTCZSiYDJbEFmZ+1nERGRaxepVMqwYbfw00/f06FDJwICGmYXyNXVjdat2/LSS6/W2Pe/96nVq7+1+zyKkiBfk8lYrr20LDvYlDWJREJ2dvWFYABmzXqa//1vA3PmPMmnn35eZjV0dbUZAZ5++nnalxTkuZr/KsNXX9P48ZPo339gpX3/978N/Pvv38yf/yZBQZXn03ZxsZWWX7hwMS1aVLRiXp3R4Uan1grr9OnTuXz5Mt9//z0//PBDWbvVauXOO+9k2rTa5+EUaTwUPj42PyurFX1yMrLIyEY7lzb2PBKVCqvFgtSxdrnxJBIJUkGK2WrmXG4c46865qFyp4WjDxmaLOLy4unsU/GG0RjoU1PJ3rAWq9FE0Nx51fbt0MoThUxCdr6OxIxCPD1tAVAyqYSIYHdOxecQnaBuVIW1VFHddyaNP/YnMu/OLvUOkDJbrKzZEgPAxIGtykq2ioiI3BiMHTuezMwMRo6sfWntqujRoxf79+/F29vHLsvm1ZQWJ7AHHx+bApeQcKnsPBcvXiA3N6esj4ODA+3bd2Tr1j+4++77q3ULUKlUfPDBUubOfZLZs5/g008/x8vLm9DQMHx9W5CamsLkyXfW6nqqWoPExASWLfuQUaNu49Zbx1Q5vmPHzqhUKrKyMhg8eGiV/W4Gaq2wCoLAggULmDp1KgcPHiQvLw93d3f69OlDy5ZNn1hYpGaUwSHokxKx6nWNeh6zRoPm7BkMGem43zISAZCVVM2wBzeFK7l6NVna7ArHIjzakqHJIib3QpMprBKlkuLjx0AiwazRIHV0rLKvUi6lfUtPjsdlczQmi66RVxIuR4V62BTWxFxu7d3wuXD/y55TaaTlaPjzUBL3jqhfAIWzgxwvVxU5BTraBLkRGepR8yAREZHrhrZtI3jnnepznNeWW28dw++/r+eppx7nnnvuJzg4hKKiIuLizmM0GsuCmepL+/Yd8PVtwSeffMTjjz9FcXER33//Da6uruX6zZgxizlzZjB37pNMnHgHLi4uxMbG4Obmztix48v1dXJy5sMPlzN7tq3/J598jru7O0899TRvvvkKOp2Wvn0H4ODgQHp6Gvv37+Gxx2YSUk02mf9iNBp5/fWXkclk3HrrGM6cOV1pvw4dOuLs7My0aTNYseITMjMz6datBxKJhNTUZHbv3sXChe+jUt0cmVvq7M3cqlUrWrVq1ZCyiDQSch8f9EmJGO3YEqkPTu074D1pCmZNMZdeeAb3ocPwvfs+u8cHuQSQq1ejqyTwKsKzDbtS9nFeHdeQIleL3MsLn3vvx6FlKyR23BC6hfvYFNbzmUy/qj0qzObTGns5r9G30wVBYPKQ1sQkqrmle8OUbA3zcyGnQMfhcxkcjM4g1M+FoV0bN4BMRETk+kWhULBs2Uq++upzvv32K3JysnFzcyc8PIKJExuu+qRMJmPRog/48MN3ePXVFwgKCmb27Gf4+OPF5fp17tyFTz75jC++WMmiRW8gkUhp2bIVjz76RKXzurq6smTJp8ya9RhPP/0kS5euYtiwW3Bxceabb75i27YtAPj5+dO7dz88Pb0qnacqsrOzuHAhFoCnn64YaFVKqf/uPffcj4+PDz///APr1v2MTCYjMDCIfv0G1jso7XpCsNYy83BMTAyFhYX07GmrjqHRaHj//feJjo6mf//+zJ49+4ashKNWF2MyVZ9o91ol85efyNu2FZd+A/B/ZHrNA+xEJpPg4eFUYW2Kz5wi5eOPkDg60erDJUjk9hUTOJF1mi9O2xIVL+r/Cm7KK8FDGqOG53e/iRUrb/d7GQ+Ve4NdR0NRpDXy9Cd7MFusfPbicBxkAiaTBavVynMr9+Hj5sCj46LwdG26t+HU7GICvOtXunDTvgTW77pIaAtnEjOK6NTai7l3dK7TXFV9ZkTEtamO5l4bo9FATk4aXl7+yO28nzUVMplE/LxUgbg2VdNUa1PTd8fT0wmpnUacWpt63n33XXbs2FH2+0cffcSvv/6K0Wjk888/5/vvv6/tlCKNjLkkwlFz+lSjn8uYnUXe7l0gk2HRFFN01P4Iz46eV3yXdiWXr0DiKHckxNWWgeK8uukSdRtzckj74jOSP3y/xr7ODnIiQtwB2H86raxdEATem9GXF+7r1mTKqsViZdnaU8xffZBLaQU1D6iGsBK/1YJiW1RpclbjpkgTERERERH5L7VWWOPi4ujWrRtgC7TauHEjs2bNYsOGDUyfPp1169Y1uJAi9UNRkmrMotU0+rkkDo4UnzgOJfni8nfttHusVCpFKbG9gV0qSKxwPKIkW0BMbtMprBKlksJDB9Cci8b0n/J/ldEt3OZcv/9MWrl2qZ3VThoKiUTAUSVDIghcTK2fwhri50KYnwvtW9q2vXIL9Gh0xhpGiYiIiIiINBy1fooWFBTgXhJIExMTQ0FBAaNH26IL+/bty+XL1ddeF2l6VCXJfa0mU431g+uL1MmJFvc9SMCsuSAIaGPPY0hLtXu8g8xmgUwsqFifuJ2HLUXXeXVcvWpo1wapszPK0DAANOdqrqXdta1NYT2fqEZdWN4XV28wc/piDlq9qbKhDc6kQa1Y+GhvhnevX25kV0cFr03tySNjIvF0taUqS84qbggRRURERERE7KLWCqu7uzvp6bYkuQcPHsTLy4vQUFt0nNFobDJFQsR+HK6qwGFIqagINjRugwbj3LkLTh07I/dtYZdlshRvB1sNZZ25YkaDVm6htHYLo69/T0yWplH6ABwjba4KmnNna+zr4aKkdUni/qPnM8sde/vbIyz55STnk/IaXMbK8HRV0cLTEXWhnt0n7X9pqI4gH1u6rhTRLUBEREREpAmptcLao0cPPvnkE7777jvWrFnDkCFDyo4lJibi7+9f9WCRZkGiUkHJlrQuPr7Rz2e1WEj/5iu0F+MJevb5MoXPHrr7XqmiVKAvX+ZXLpUzr/uT3N76VuTSqkulNjRXFNZou17IekTYrKxHz5fPyhAe7A5AdEJuwwpYDRqdiRc/28/XW2LqpWSevZTLuz8cK7MaXxYtrCIiIiIiTUitFdZ58+YhCAILFy5EoVAwc+aVlAxbt26lc+e6RQ+LNC6laZn0l2tfP7i2CBIJhpQULEWFFJcEelmM9vk89g/ojUywJXbO0VZU7HQmHcczT7MreX/DCVwDDm3aIshkmNRqjOlpNfbv3s4XgJhENUXaK9ddmsM0OlHdOIJWgqNKRsdWXrQNckNvrLs7iNliJfZyHoUaMfBKRERERKTpqXUCr+DgYLZu3VpWMOBqXn31VXx8alfVQqRpkLq4YNFoMPyn5nFj4TVhEoIgIHFy4vIH7wEQ/OwLNY6TSqW0cW9FjDqOlOI0WrqXT8acqc1m9ZnvUEmV9A/ohVRSddWShkKiUODQNhzNuWiKz0WjqKEUnp+nI6F+LiSmF3LyQjb9O9p2HdqFeiBgSzWlLtTj4dI0Ncgfv709cln9gr5KMwXkFdkU1pSs4gYr/yoiIiIiIlITdX6K/VdZBYiIiMDT07M+8og0ErKSxMamnJwaejYMTlHtcYyMQuLoiPZ8DNqYc3Yry2arGYCNF/+scCzIOYBWbqH08e+B3mxoUJmr42q3AHvoU6KkHou94hbg7CAvK216LrHp3ALkMglavYl/T6Rw5mLd/v6uTgoevDWC5+7ugkQioNWbyC2oWOBBRERERESkMWjaXDsizYZzV1sqMul/StY1Juptf5L8wXsoAm1R6kXHjtZqfJGxop+kRJDwTPeZ3BE+Hke5Q4PIaQ+lCqs25hxWs7nG/n072BTWs5dy0Ruu9I8Ms7kFnEtoOrcAgL+OXObbrefZtL9iujB7GdIlkMgwT7qH+9C/gx8WMcBSRERERKSJuHlqet3klKa2MuU2jYUVwKwpxpSdjUNkFMEvvIKqTRu7xnX17URc3kUAigxFOCucyx03mo3E5l0kW5vD4KB+DS53ZShDw5A4OmLRaNAlJpTLvFAZrQLd8HZTkZ2v48ylHLpH2Pxao8I82XIgiehEdZNuqffv6M/Bc5l0aeNd5/NarVZyC/SM7hNCmF/TvfiIiNyonDlzmp9++p7Tp0+Qn5+Pq6sbnTp15u6776dDh041T1AF69f/ikql4rbbxtV67LFjR5g9e4ZdfUtLh1ZFWloqd9xxOy+//HqdZBERuRpRYb1JkJf4Fpvy8rAYDXaXS60Prv0GoAoNxTGqAxKl/f6aA/x780vsbwDsTjnA6Ja3lDuepy9gxckvkQpS+vj3QClt/GsRJBK8J05G4uSEws+v5v6CQPd2vvx5MIljsVllCmvbQDfkMgnODnKKdSacHZom24Gnq4q3pvWql4J85lIuS345SQsPBx4YFYHJbKVT69rV0BYREbGxdu1PLFv2EZGR7Xniidn4+fmTkZHO+vW/8uST05kz5xkmT76rTnNv2PArbm7udVISIyLasWrV1+XaXnnlWQICgpg5c26d5BERaQhEhfUmQersYkttZbGgjT2PU/uOjX5Oha8vCl+bomYqLkZz8gT6lMv43HF39bJKpQgIWLFyMP1oBYXV28ETL5UHOTo1F/Iu0d4rotGu4Wrchw6vVf8eET78eTCJkxdyMJktyKQSFHIpH88agIOy6b96Viscj8vi0LkMpo2JqnUgVoivzdKdodbywU8nCPJxEhVWEZE6cOrUCZYt+4g+ffqzaNFiZLIr94Phw0fy8svPsXTph7RtG0GnTl2aVDYnJ2c6dCj/fJDLFbi4uFRob2pMJRUUr14vkZsH8a9+kyAIAoJUitViQXfxYpMorADFZ06T9evPyH19KT5+DAD3IcPLLL5VIZfIMVgM5OryKhwTBIEIjzbsSzvM+dy4JlNYrSYTOX9sRHs+hsA582q0GrcNcsfVUU6Bxsj5pDzat7QFJDaHsgpgxcoP22NRF+rpFu5Dr8gWtRrv5qzE3VlBXpEBDxclAd5OYqYAEZE68P33axAEgWeffbGC8iWTyXjmmRe4887xfP/9N7z/fhcAvvzyM77++gu++up71qz5kiNHDiEIMGDAIJ56ah4eHjb/+ClTxpFekn5vwIAeAPj5+bN27cYGvYaLFy/w+ecrOHHiOAaDnpCQMO66615Gjx5b49jLl5P48svPOHLkEMXFRQQEBDJp0p1MnnxnWZ9S14T5898kLi6Wv//eRk5ONt9//yuurm58+eVnnDhxlIyMdJRKFa1atWbatMfp3Llr2RypqalMmjSWJ5+cg0QisG7dL+TlqWnVqg2zZs2roICfPXuGb775kjNnTqHTafH29qF//0HMmfNMrWQXaRxq/eSMiYmhsLCQnj17AlBcXMzixYuJjo6mf//+zJ49W3yAXaNIHB0x5+ejb4JqV2XnVCoxpCRjzs/HMbI9mnNnyd+9E+9JU6odF+YaTGxevM0sWAkRnm3Zl3aYGHVcY4hdOVIpBXt3Y8rNRXshDqf2HartLpEIdGnrw66TqRyNzSpTWAHMFguX0gpp6e+CVNI0sY9SiYRRvULIL9LT0r9uPqihLVzIK8rh1t4hjOgR3MASiojc+JjNZo4dO0JERCS+vpW/NLZo4Ud4eDuOHTuM2WxGKr2Svu/ll59j2LBbmDBhMpcuxbN69SouXbrI559/g0wmY9Gixcyf/wLOzs7Mm/ciAApFw7oeJSUlMGPGNDw8PJg791nc3Nz4888tLFz4Brm5Odx330NVjr106SJPPPEILVr48dRTc/Hy8uLgwQMsXfoB+fl5PPLIY+X6f/bZp7Rv35Fnn30JiUSCh4cHeXm2oNWHH34UT08vtFotu3btYNasx/n44xV069aj3BwbNvxKSEgYs2fPA2D16lU899wcfv31fzg723aODh7czwsvPE1oaEtmzXqaFi38SEtL5dChA3WWXaRhqbXC+u677xIVFVWmsC5ZsoRff/2V8PBwPv/8czw9PXnggQcaXFCR+iNzc8ecn48xK6vmzg2EqnUb/KY/hlOHTmhiztkU1r178Lp9AkI12zqjwoYReyIeMxYMJgMKWXk/1QgPWwBXSlEahYYiXP4TmNUYCIKA55hxCIIEZZB9ylq3cJvCejwui/tHhiMRBKxWKy+uOkBOgY5XHuxO6wC3Rpb8CiN71k/JDPVz4WR8DpdSC7iUVoCTSoavh2MDSScicuOTn5+HTqfDv4Z8zgEBAZw7d5aCgnw8PK687A4ePJQnn5wDQK9effD29ub111/hn3+2M3LkaMLD26FUKnF0dGq0Lfwvv/wck8nIsmWraNHC5tPft+8AiooK+frrLxg/fnKZIvhfPvlkCY6OTqxYsRonJ1ufnj37YDQa+P77b5gy5W5cr8pmExgYxNtvv1duDldXN5599sWy381mM7169SEtLY21a3+uoLA6Ojry/vtLyhR/b28fHn30IQ4c2Mstt4wC4KOP3qNFCz8+/3wNyqt2z8aMub3Osos0LLU27cTFxdGtmy1FktVqZePGjcyaNYsNGzYwffp01q1b1+BCijQM8lJ/0rymS6kkSCS49umH1NkZx8gopC4umPPzKD59stpx4e5XovD/Tt5V4biLwplAZ1vqqFj1hYYVuhrcBw/FbdBgZG72KZmRoR44KKXkFxm4mFoA2BTf0kT80U2c3gpsVaq+/COa3/dcqvXY0uwAsZfzeOubI+w8mdrQ4omIiHD15lL5HcsRI0aX+3348BFIpVKOHas+Yr8hOXbsCN279yxTVksZPXocOp2OM2dOVTpOr9dz9OghBg0aglKpwmQylf306dMfg0HP2bOny40ZPHhYpXP99ttaHnnkPoYN68fgwb0ZMqQPR48eIjGx4n2tb98B5azUrVu3BShznUhKSiQlJZmxY8eXU1brK7tIw1JrC2tBQUFZ0YCYmBgKCgoYPdr2Berbty/ff/99gwoo0nAoAgKBw1g0miY9rzEnm7TPV2HKzcG13wDUf24hf9dOnLt2r3KMRCIpC7w6lXmW0WG3VOgT4dGGlKI0YnIv0L1Fl0a8gitYrVbUf25Bcy4a/+mPI3Vxqba/XCahU2tvDkZncOx8Fm0CbYpuZJgHR2OzOJeQy7h+YU0g+RUycrXsPZ2Oq6OcMX1DkUntf2+NCvPgk7kDORidwffbYknJqpgrV0REpGrc3NxRqVSkpVX/speWlopKpapgsfPyKh/oKJPJcHNzJz8/v8FlrYqCgny8vLwrtHt7+5Qdr2qc2Wxm7dqfWbv250r75Ofnlfu9svP89NP3LF/+MRMmTGb69Cdwc3NHKpXwxRerKlVYXV3LGxgUCtuOnV5vK35S6mLg4+NbqUx1lV2kYam1wuru7k56uq1i0cGDB/Hy8iI01FY+02g0YhWTiV+zOJTkYrUajVgsFiRN5Tvp6oYhJRmLTodDeDhWkwm3QYNrHOehcidXp0Zj0lV6vJ1nW/65vJsYdVyTBf8IgkDB/n0YUpLRnD+HS49eNY7pFu5jU1hjs7hjaGsEQSAqzLbFdyElH73RjFLe+CVmS+ncxovh3YLoHdUCqaR2a6aQS1HIpQT52LbDkrOKGkNEEZEbFqlUSrduPTh4cD+ZmRmV+rFmZmYQGxtD7979ylkGAXJycsopViaTifz8PNzs3PVpCFxd3cjJya7Qnp1tczdzc3OvdJyLiytSqZRRo25j0qQ7Ku3zX1eJym7r27ZtoWvX7jz77Evl2jWaur1Au7vbAtaysjKr7FMX2UUallorrD169OCTTz5BrVazZs0ahgwZUnYsMTERf3//hpRPpAFRXpW435SRgaKJ/lYSuRz/GTNRBAQi9/TE+aoozuro6B3JzuR9lVa8Amjt1hKpICVXpyZbm4uPY9OkWHKMjLQprOei7VJYO7byRCaVkJmnJSWrmCBfZ1p4OODpqiS3QE9cch4dWjZdeiiZVMJ9I8MBsFislT4QquNSWgGn420Pq9wCPRqdEUdV0+STFRG5Ebj//qkcOLCPDz98l0WLPiinlJrNZj744F2sVisPPDC1wtjt27fQrl1k2e9//70ds9lM16t2rORyRZn1sDHo3r0nu3b9S3Z2VplVFeDPP/9ApVLRvoosNCqViq5duxMbe57Wrdsil9f1viEg/08u8QsX4jh79nSVgWzVERISSmBgEH/88T/uuuu+Mgts48guUldqbWKbN28egiCwcOFCFAoFM2fOLDu2detWOnfu3KACijQcMkcnhBL/HENu09WyB3Dq0BG5pydmrRar1Yq5qIi8f/+ptsxpNx/bZ0ln1qE1aCscV8mURHq2pYNXOwwWQ6PJ/l8cI9sDoImOtqu/SiGjQ0mGgGOxNguEIAhEhdramrpMK9hcG3799wLPfLqXrLyKa1sdJ+Ky+eNAEgq57faRLLoFiIjUik6dujB79jz279/Lk09OZ9u2LZw8eZxt27Ywc+ajHDiwl9mz59GxY8Xn6c6dO1ixYimHDx/gl19+5L33FtKmTTjDho0o69O6dRvi4+P4++9tnDt3lvj4K37+gwf3Zs6cJ+ol/yOPPIpMJmPWrMfZtm0L+/fvZcGCV9m3bw+PPPJYlQFXAHPmPEtGRjpPPjmdzZs3cuzYEfbs2cXPP/9gd4Wt/v0HcvjwAb788jOOHj3Mhg1reeaZp+pl4Zw37wXS09N4/PGpbNmyiWPHjrBlyybefHN+g8ouUndqbWENDg5m69at5OXllfmylvLqq6/iU0N+TZHmRRUSijYuFktxYZOe12q1krZiOUWnThDyymukfrIUkzoXmYcnzp27VDomxDWw7P970w9xS0hFN4InOj/SWCJXiWNEBEgkGLMyMWZl1ZhTFqBruDcnLmRzNDaL2wfYXDOiwjzYczqtWQKvBEEgKb2Q/GIDB86mM65/S7vHlgaMSUpMsylZRYQHuzeGmCIiNyxTptxNu3bty/wx8/PzykqzrlixusrSrAsXLuarrz5jw4Z1CILAgAGDmDVrXjmL37Rpj5OTk8177y1Eoykul4fVbDZjrsZQYA8hIWGsWvUln332KR999B56vZ7Q0JZ2lWBt2bJVSS7Z1XzxxUrU6lycnV0IDg6mT5/+dp3/wQcfQafTsWnT7/zww7eEhbXk2WdfYteufzl+/Gidrql3774sX/4Fa9Z8wdKlH2AwGPDx8WXAgEENKrtI3RGs16HTaXFxMaNHjyYjI4O1a9fSseOV7YedO3eyZMkS4uPj8fPzY+rUqdx33331PqdaXYzJZKn3PM1N+pdfULB/L14TJ+M1pn61nWUyCR4eTnavTconH1N88gQ+d9+LKScH9fY/cerSlcCn5lQ5ZtY/L2LBQhu3ljzdvaJVwGq1kqXNJlYdT7+AXkiEpvHLTXp3IboLcbR48OEK/riVrUuhxsDcT/ZgtcJ7M/ri4+5AfpGep5fvxcddxdvTeyOXNZ0fK9gi/Yu1Rjq18apVLlh1oZ5vtsag1ZuIS85nSNdAHhxlX/GG2n5mbibEtama5l4bo9FATk4aXl7+Fbaim4rSwgGbNv1Vzlgkk0nEz0sViGtTNU21NjV9dzw9nZDaGfhbp6d7fHw88+bNY8CAAXTo0IGzZ88CsHz5cg4cOFDD6PqzYsWKSt8Qjx8/zpNPPklUVBRffPEFEydO5O233+bXX39tdJmuFyROtpyZmphzTX5u7wmTCF2wCI9bRuI6cDBSF1eUAYHVBuo5ym3yphVnVHrcYrXw3uFl/N/59SQXNV2KJcfIKAA0Mfa5Bbg4KogosUKWugW4OStZ/EQ/3pvRr8mVVYDwYHe6hvsgEQSKdUa7x3m4KJl7R2eGdLVZwMXAKxERERGRxqbWCuu5c+eYMmUKhw4dolevXuUUx+LiYn766acGFfC/xMfH8+OPPzJr1qwKxz799FOioqJYtGgRffr04cknn2TKlCksXboUi0V8ywJbhgAAfWJCk59bGRyCMiAAi9GA3NOTVh8swXvSlGqj+/2dbNGwxabKU3FJJVIiPcNp694Kk6V+21y1oUxhPReN1c7PVrdwm+vA0dgrhRu83FQNL1wtOJ+k5pUvDvLFRvsU76spzRSQklUsZgcREREREWlUaq2wfvDBB0RERLB9+3bef//9cg+qTp06cfp04ybOXbhwIXfffTctW5b3uTMYDBw4cIAxY8aUax83bhxZWVlE2xkgc6OjDAoBwKKrPFVUY5Oz6X/Ez51N/q5/EUoiY00FBVUqfW2vKiBQZKjckjetw/3M7TaDVm6hDS9wFTi0ao2gVGIuLMRgZ6nbUoU1Pjmf/OIrQWJWq5W0nOYJXHJzVpKeqyEuOQ+NzmT3uMMxmazYcBoB0BlM5BU1XdCbiMjNyLRpj7Nnz5EKsSMiIjcLtQ66OnbsGIsXL8bBwaHCtry3tzfZ2RVzszUUW7duJSYmhmXLlpW5IZSSlJSE0WikVatW5drblKRyio+Pp0OH6mu/V4e9PhbXOk7htgofWCxITAYkqrpb+ErXpDZrI3dyxKrXobsQh+y220hd8zV5u3cRMudpnDtVDDIY1WowmxO2A7A//TCjWw2vdN48XT4xuRfo1qITCmkTpBuRKXCKaEfRqZPozp/DqWVY2aGq1sXX05FWAa5cTC3gVHw2Q7sFYTJbeH7FfnIKdHw4sz8+Hg6NL/tVBPk6M/fOziUVuey/HSjkEjLUWvy8HHh7eh8UduaRrctn5mZBXJuqae61sVgaP8dzXSjdnBKEqytjiYC4NtXRHGsjlQrIZPX7/tZaYQWqzD+Wn59faf6yhkCr1fLuu+8yb968SlNmlFb5+G9VkNLf61sFxNW1aRWJxsLNrR2ldUAMp47hP2pEtf3toTZr4zxqGL5dOuDcpjWCRILa2YE8s5ni/bsJHty3khFOSAQBi9XK+bwL3Otxe4UeVquV+ZsWkaXJxdlJxcCwmnOjNgSmkcMpbtsK717dcPZwqnC8snUZ0CWQi6kFnIzPZdJwW6CSr6cjOQU6LmUWE96qYlWXxmZ4b5vslzMKCfC2zwG+U4Qt12GWWoeHhxMyqQRJLYoQ3Cjfp8ZAXJuqaa610emkZGdLGuSh2xiILzlVI65N1TTF2lgsAhKJBDc3R1T1MJBBHRTWiIgI/vrrLwYPrphiaPfu3bRv375eAlXFypUr8fLyYtKkSdX2q8ofsr5VkAoKtJjNN4YfrMzDA5NaTfqOnah69avzPFKpBFdXh1qujQx8AlCrizEXFeHQZwBs2kzOoSNkXkpBXsl2l4vcmXxDITnFatTqyrfO+/j3YGP8Nv6M3UkHt8b5DP4XWYcuuHXoghHKyVXdukSFuANwMi6LlLR8HFUyIoLdOJeQy+GzafSKaHqFFWDpryc5ej6Lp+/qTNe2NafpklmtuDjKKdQYmfb2dqLCPJgxoeYdjLp9Zm4OxLWpmuZeG4NBj8ViwWy2XlNR54JgWxuz2SJaEf+DuDZV05RrYzZbsVgs5Odr0Gorxpm4ujrYrTjXWmF98MEHeeaZZ3BwcGD8+PEApKWlceDAAdatW8eyZctqO2WNpKSk8NVXX/Hpp59SVGTzY9RoNGX/FhcXl5Wl+68ltaCgAKhoea0tZrPlmrpR1QeH8AgKDx5Al5DQINdU27UpPn2K9K++QBkaRtDcZ1C1boMu/gLqXbvwvG1shf4dvduzJ/UA+YbCKs/Tu0UPNsVvJ1Z9kZT8dFo4VV0TuiEpPnOKohMncOs/AFXL8u4ola2Lr7sD/l6OpOVoOHY+kz7t/WgX4gFcIjohF4PRXJbftCnxclUhKcnN2tHOqluhLVw4cymXvCI9SRlV/20q40b6PjU04tpUTXOtjdl8bWo8pcqGqJBVRFybqmmOtWmIl71a24Nvu+025syZw48//siUKVMAmDVrFkuWLGH27NkMGzasXgJVRnJyMkajkccee4yePXvSs2dPZsywVZV48MEHefjhhwkJCUEul3Px4sVyYy9csFX4aN26dYV5b1ZcSxIhW7RaTCUKfVMi9/bGXFiIPikRq8lUlsc0f/fOSoOvOni3A8BoNmCxVv6B91C5097L1m9v6qFGkrwiBfv2kf/vPxSdPGH3mNLgq9L0Vq0CXFHKpRRqjCRnNk+KqNG9Q1j8ZD/G9A2ze0xoSQGBTq09ee4e+8rtioiIiIiI1IU6+bDOmDGDCRMmsHv3bnJycvDw8GDAgAEEBgbWPLgOREZG8u2335ZrO3fuHO+88w5vvvkmHTt2RKFQ0KdPH7Zs2cLUqVPL+m3atAkfHx+ioqIaRbbrEYeIdiCVgtlM8ZlTuPUb0KTnV/gHEPT8S7ZIe5kMlx69yPrpR7CCSa1G7lXewtfeqx0SJFiwcDj9OL39u1c674DA3pzJOcfB9KOMa30rckmdPt61wqVnT6TOzjhG2e+G0C3chz/2J3LqYg4GoxmFXEp4sDunL+YQnaAmpIVLI0pcOW7OtpK9+UV6svJ0tAlyq3FM78gWhLRwoaW/Cy6OzZNMXURERETk5qDOT3Q/Pz/uuOOOhpSlSlxdXendu3elx9q3b1/mNztz5kzuv/9+5s+fz7hx4zh27Bi//vorCxYsQFKLSj43OhKJBJc+/SjcuxtDsn0pmRoax/AIrFYrxpwc5F5ehLzyGnLfFgiV/J0kggQrtr2Lncn7qlRYozwjcFe6kafP51TWGbq36NKYlwCAc9fuOHetXJ6qCPNzwdNVSW6BnrMJuXRt60NUmIdNYU3M5dbeIY0kbfWcT1LzwU8ncHdW8t6MvjUGUQX5OhPk68zGfQkciclkbL8werZrGlcMEREREZGbi1prcTt27OD777+v9NgPP/zAzp076y1UXenatSsrVqzg9OnTTJs2jXXr1jF//vwmU6yvJ5xKlHzNubM19GwcTHlqEl56noTXXsZiMKDw8y9TVitLQi+V2NImpRanVTmnVCKlr39PoGndArRxcWT9+jOa2PN29RcEgW5ty7sFRIV5ApCWXYylmZyuWvq7olJIcXdRUKCxL6+qwWgmMb2Ay5lFJKYXNrKEIiIiDUFSUiLz5s3illsGMHbsCD7++AP0+ppzc//99zZeeeU5JkwYzYABPfjxx+8q9DGZTCxZ8j6jRw/j7rsnsn//3gp9Zs16nF9++bFBrkXk5qHWCuuqVavKAp7+i0ajYdWqVfUWyh569+7N+fPn6dixY7n2wYMH8/vvv3PmzBn++usv7rvvviaR53rDsZ3NRUJ/+TL6tKqVwMZC6uaO1WIGiwV9iZVXE3OO5CUfoN62tUJ/fweb5c5cQ1Wpvv49ERA4r75Alian4QWvhIID+1D/uYWio0fsHlPqx3oiLhuzxUKgjxOvT+3Je0/0a5agKwCFXMrCR/vwygM9cC9xEaiJ5etPcyzWlntZLNEqInLtU1hYyJw5T6DVFvP22+8zc+Yctm/fwnvvLaxx7I4df5OamkL//gOr7LNp0+/s2bOL+fPfpG/fAbzxxssUFFwJhv777+2o1WomTbqzQa5H5Oah1grrxYsXq/QHjYqKIj4+vt5CiTQ+MldXhJJ8uvn//tPk5xcEgcBZT9P64+U4lBR7MGZlojl7hvxd/1awso4KswXzWbBgslRdkcnLwYNIr3AA9qU1jZX1SplW+63VbYPdcHaQU6wzEZuUh0QQCPVzaTZltRRXJwV6g5ndJ1PJL9LX2P9qf9sUUWEVEbnm+f33dRQWFvDOOx/Rp08/Ro8ey5w5z7Ft2xYSEi5VO3bBgnf4+usfee65l6vsc+TIQSZPvpP+/Qcyc+YcLBYrZ8/aKmDq9TpWrFjKnDnPIJM1foyByI1FrRVWg8GAsaQefWXHdM1U8lOk9ij8AwAoPtu45XSrQhkcjESpxJCVidVsxqVnbwSlCmNGBroLceX6dvCOLPv/obRj1c47JKg/AwP70qMJfFgBHNtFgiBgSE3FlKe2a4xUIqFLW1vO1VILZSmFdm7HNxbL15/i6y0x7Dlds+U9zM8FmdSmZOcU6NHoKr83iIiIXBscOLCPHj16lSvxOmTIMBQKRaXb91djTyyI0WhEqbTt0MhkMuRyOQaD7b7w3XdriIiIpGfPymNSRESqo9YKa8uWLdmxY0elx3bs2EFYWFh9ZRJpIpy7dgPAmJlZqd9oU5D84fskvPQ82tjzSFQqfO+5j6DnX0LVpm25fvKryq3+c3l3tXO292rH3RETCXT2bxSZ/4vU2RllSCgAmnPn7B5Xlt4qLguL1YpWb+KVLw7w9Cd70eqrtiI3Nr2j/PB1d7Ar8r9LW29WPjMYT1fbAyo5q/LCDiIiNyJWqxWdTttsP3W5byckXCI0tGW5NoVCQUBAEImJ1VtY7SEysj1bt24mNzeHLVs2UVxcRHh4BGlpqaxb9wtPPTW33ucQuTmptU1+8uTJvPPOO3h7e3Pvvffi7e1NdnY2//d//8fatWt58cUXG0NOkUbAbdBgcn7fABYLmvMxOLWLrHlQAyPz8gKJBH1KMo6RUbgNqNo3SibIMFlN5OpqtmKqdXlsT/qXIkMxj3RofD9mx8go9IkJaM6dxXOgfWnC2od5oFRIURfqSUgrpFWAK2aL1VaGNimvzALb1PTt0IJ+Hf3sck+QlVQoCfJxJrdAT0pWEeHB7o0soYhI82O1Wnn22VlERzdP4CpAVFQHPv54ea3GFBYW4OxcMXWei4tLWaGd+jBlyt3s27eH228fhSAIzJjxFP7+Abz88nNMnnwnAQGNk/5S5Man1grr/fffz+nTp1mxYgUrV65EKpViNpuxWq2MHz+eBx98sDHkFGkEZG7uSFQOWHRaCnbvahaF1ev2CfhMuQups3NZm8VooOjoEQS5HJfuPcvag10CuVSQiMlas/XRbDWzM3kfAgLjtaPxcvBsFPlLcYyMQr11M5pz0XZbPeQyKR1beXEkJpNjsVm0CnAlKsyTTHUK0Ym5zaawSiUSzBYLJ+JzSM/R1Jhm6+ylXPKLbG4MooVV5OaieX3O60rl76LWKtprh7OzM5999jWpqSm4uLjg6urGkSOHiImJ5rXX3iIpKYF3332buLhY2rYN56WXXiM4uHlS+YlcX9RaYRUEgffff58777yT3bt3k5ubi6enJwMHDqRHjx6NIaNII6IMC0Mbcw5tbEyznF/uaSsSYCopqStzc6Ng/z4yv12Dws8f5249EEruooOD+nIpOhGz1YLBbEAhrXrL2tvBi7EtRxLmGoKHyr3Rr8OhbTiCTIZJrcaQlgaebWseBHQP9+FITCZHY7OYPLgVUaEe/Hs8hXMJ9vnCNhap2RqWrT2FVCLQr4Mfrk5Vr/XZhFwSM2wprcRMASI3C4Ig8MEHy+xKB9VYKJWqkvuj/a4BLi6uFBZWTEFXWFhUwVWgrgiCQGBgEGBLc7V06QfMnDkXlUrFggWvERXVnsWLP2blyk94663X+PzzNQ1yXpEbmzqH6fXo0UNUUG8AXHr0RBtzDpNajcVkQtIMkZvZv28gd9P/8Bw9Bu9JU3Dp2Zusn37EkJ6GNi4Wx/AIADp5X6kmdSTjBP0CelU77+iWtwBgsVqwWC1IhMYrHiFRKFC1aYs25hzF0dHQ3j6FtVNrL2RSgYxcDak5GtqFeiAAKdnF5BXp7U4v1dAE+zrTqbUX/l6ONT4Kw/yubC8mZxVjtVrLXjJERG5kBEFApXJobjFqRVhYywq+qgaDgdTUZMaMub3Bz7d+/S+4ubkzfPgIiouLiImJ5uWXX8PJyZlJk+7gwQfvRqMpxtHRqcHPLXJjUa8neG5uLqmpqRV+RK4fXPv2K/t/c1lZFX7+YLVizMoEQOrggEuvPgDk775SiEIpUyKUbMGdyjpj19z/Ju/l9f3vcTrb/mCouuJUUp61uBY+bQ5KGZGhNneFY7FZODvICSlRAJvbyjr3js7cNawtbtVYVwFCS+QVBJg4sCVmS/ME8ImIiNRMnz79OHr0MPn5eWVtu3btwGAw0Ldv/wY9l1qt5ptvvmTu3OfKtZdmE9JqxaxCIvZTa4W1qKiIV155hS5dutC/f3+GDx9e4Ufk+kGiVOHYsRMA+qSkZpHBuUtXWr73If6PP1nW5jZoMABFRw5jLr7iF9nC0VZAIN9g39azWpdHrk7N3tSDDShx5Ti274BTx044d+pUq3HdI/5b9coDgOjE3IYVsA4kpBewZss5Yi/nVdnH190BB6UMqxXCg93LArFERESuPcaPn4yzswsvvvgMBw/uZ+vWP/j448WMHDmasLArLgHvvLOAwYPLp5+6dOkiO3b8xY4dfwFw8eIFduz4q8p0WJ99tpzhw0fSpiTri5OTMxERkaxevYrDhw/wxRcriIyMEq2rInZR6/3fRYsWsWnTJqZMmUJERAQKRc2pb0SubZzad0Bz+hSac9F43npbk59folQiUSoxa7WY1GqUAQGoWrZCERSMIfkyBQf24TF8BABhrsGkazLI1GTZNXe/gF78lbST6Jzz5OrUeKo8Gu06VKFhBM6Zh0xWO4WtSxtvBAES0wvJztcSFebJlgNJXEjOr3lwI7PzRCq7TqahN1qqjP4XBIHQFs7EJOWxcW8C/Tr60bWk9KyIiMi1hYuLC0uXruTjjxfzyivPoVKpuOWWUTzxxKxy/SwWC2azuVzbP/9s5+uvvyj7fevWP9i69Q/8/PxZu3Zjub4xMefYs2cXP/64tlz7q68u4L333ubll5+jTZu2vPrqgga+QpEblVorrDt37uSZZ57hoYceagx5RJoBx0jbVrbmfAwmTTGyZnjbLT5zitTly1AEBhH66hsIgoDHLSPRJSaUVZICCHDyA0Bn1mMwGVDIqn9hauHoQ7h7a2Lz4tmfepgxrUY26nUYc3MoPHsai78vknYd7Brj6qSgbaAbscn5HI/NZnCXAJ67pyttAt0aVVZ7GNIlEIPRzOAu1aei6Rbug85g5mhsFnKZRFRYRUSuYUJCQvnoo+rTYb3yyhu88sob5dqmTXucadMet+sc7dpFsmnT9grtYWEtWbnyS7tlFREppdZ7d3q9nvDw8MaQRaSZkPv72xwQTSYK9lSflL+xUIaEYTWbseh0WEr8m9wGDKTFfQ+gvCpvX+8W3cr+vytlv11z9y8JztqXdhizxVxD7/pRfPIEad+sIe2PzbUa1y3C5upwLDYLhVxKZKgH8lpaahuDUD8XHh3Xvsbcqrf0COauYW3oE9WCqLDGTSEmIiIiInLzUesn4uDBgzl69GhjyCLSTEgkEmQl6aWKjjXP31bm6krLd94n7O13kKhU5Y6ZNRo056IBcFZdydd6Xl2+fGtVdPbpgJPckTx9PtG55xtO6EpwjGyPY0QE7l271Gpct5Kcq7HJeRRcVZrVaGpcBdseirRG1u2MZ/H/Ha82x2xEiAePjouif0e/JpRORERERORmoNYK6xNPPMHmzZv5+uuvSUhIIC8vr8KPyPWHY6StaID+cvMEXgHIvX2wmkxo4y+UtRkyM7n47FxSPvkYs0YDgLPc5rKQrbUvKEkuldPbrzsAe1MPNbDU5VH4+RH20isETZ5Yq3He7g6EtHDGaoUTcdnkFel5+9sjPPPpPizNHHUvlQhsP3KZc4lq4qrxq/1k3Sme/GgX63ZeJLdAjP4VEREREWk4aq2wjh07losXL/L+++8zevRo+vbtW+FH5PqjNCrfqtdjyLYvoKmhMRcVcXHebC6/uxBToa1EoNzHB7m3N1aDgcKDBwAIcgkAIFtnfxR9qVvAmexz5OkbN5jJarGQtXM36T98X6tx3cKvZAtwdVSQlqOhSGskIb1iku+mxEEpY/Kg1jw5oQOtAlyr7KfRmdAbzWw+kEhscl7TCSgiIiIicsNT66CrmTNniknBb0AcWrUBqRTMZvJ3/ovP5DuaXAapszNyH19M+fkYMzKQubgiCAJuAweT88dGrCURq23dWhGTG4fFaotilUqlNc7t59SC1m4tic+/xP7UI4xu2Xjp1wyZmcR/vAwsFpx69MKhdRu7xnUP9+G33ZeITshFbzQTGerBsdgsohNyq1UUm4IRPYMBW/10s8WCVFLxXTfUz4XzJemvkjOLIapCFxERERERkTpRa4V11qxZNXcSuS5R+PlhSEmh+PTJZlFYAQJnP43U1RXhKoXIbdAQ3IYMQyKXAzZr6cZLfwJwIe8iEV72VZUaENib+PxLZGmzG17wq1D6+eE7dAiZf/9D9vq1BD37gl0veQHeTrTwcCBDreX0xRyiwq4orGP7hTWqzPZwMDqDjfsSGNIlgFt6BFc4PqhzAFarle1HksUSrSIiIiIiDUrzhyGLXDM4dewMgCEtvdlkkLm7A6CNiyvLFiBRKsuUVYvRgIvSBYXE9vuZXPurc3Xx6cjrfZ7nwai7GlboSgi5504EmQzt+Rg0dla+EgShnFtAZKgtZ+yFlHz0xmsj+Co1u5j9ZzMqPR7g7UT3kmwHKaLCKiIiIiLSgNSpcLzZbGbXrl3Ex8eXlVgrRRAEZs6c2SDCiTQtboOHot66Gcwm9OlpKP38m0WO5MXvoo2Lxf/xJ3HpafM9NWu1ZH73DcXRZ2j17mIcZA4YDEaOZp5kcttxds2rkMrxdfRGY9RyMT+BDt6RjXYNSh8fPIYNJ3fbn2SvX4tjZFQ5q3FVdIvwYcvBJE7F5/DIbZF4uChRF+q5kJxP+5bNmy6qb/sWSAToHVV1FgBnB9uLRE6BHo3OhKOqTrcYERERERGRctT6aaJWq7nvvvu4ePEigiCUpbm5estTVFivTxQ+PiiCQzBcTkIXH99sCquqdRv0yZcxF10JNpKoVOgSE7AUFVFw6CCOCgfyDQXk6wtqNXe+voDX97+H2Wrm7X6v4KZ0aWjxy/AeOw71zp3oExMoOnYElx69ahzT0t8Vd2cFeUUGYpLURIV5sPd0OtEJuc2usDqq5AztFgRAocaAi2PFog3fbr1i8U7JLqJtkHtTiSciIiIicgNTa5eAJUuWoFQq2bFjB1arlV9++YVt27YxdepUwsLC+PfffxtBTJGmwrljJwA0MdHNJoPnbWNpveQT3IdeCYwSBKEsk0H+rp1Eel4pXvHf8oHV4aZ0Jcg5AD9HX/L0eQ0mc2XIXF3xGDkKgOwN68uCxqpDIgh0LXELOHo+qywJf3SiuvEErQXFOiPv/3iM51buQ6MzVTge6nclOCw5q7gpRRMRERERuYGptcJ64MABpk6diq+vzVdNIpEQEhLCCy+8QL9+/XjvvfcaXEiRpqO0DGrxqVNYLJZmkUHq6AhSKfrLlzGkp5W1u/brb2tPuMRQ6ZXI+xNZp2s1/xOdH+blXk8T6loxcKih8Rh5KxJnZ4wZ6RTs3WPXmO4lCuuJC9m0D/Nk1qSOPHd3l0aU0n4clTIKNEaMJkulqavC/K5YrMXAKxGRa4/k5MssXryIqVPvZfDg3jzwwJ12j92yZRP33juZYcP68cADd/LPP3+VO24ymViy5H1Gjx7G3XdPZP/+vRXmmDXrcX755cd6X4fIzUetFdb09HQCAwORSqVIJBK0Wm3ZsaFDh7J3b8UPqMj1g7JVKwAsxUVoTp9sNjlyfltP4puvkrt1S1mbzMUVl262AgDG/YcRsLmhHM44Uau5neSOmK1mjmacJLHgcoPJXBlSBwe8brP52OZs/B2LwVDDCAgPdsdJJaNQYyQtp5iu4T44quSNKqe9CILAw6PbsfiJfnRp413heMjVCmumqLCKiFxrXLoUz/79ewkKCiIsrKXd43bs+IuFC99g0KChfPDBMrp378Xrr7/EoUMHyvps2vQ7e/bsYv78N+nbdwBvvPEyBQVX8l7//fd21Go1kybZrySLiJRSa4XVw8ODoiLbg8jX15fY2NiyY/n5+bXanhW59pAqVUicbJWkCprx5cOxXSSCTAaUr/LkNmgIANq4WFQSmw9lUmFyref/PX4LX539gb+SdtZX1BpxGzoUmacnUjc3zPk1Fy2QSSV0LlEGj8ZeKeJQXVnUpqR1oBuerioKNAbUhfpyx/w9HZHLbLcVk7l5LPQiIiJV07//INav/4O3336f8PB2do9bvXoVQ4fewowZT9GtWw/mzn2Wnj17s3r1qrI+R44cZPLkO+nffyAzZ87BYrFy9qxtB0yv17FixVLmzHkGmUwMxhSpPbX+1LRv3564uDiGDBnCoEGDWLFiBc7Ozsjlcj766CM6d+7cGHKKNCGqlq3QnDmN9kJcs8ngEB5B64+XI1GpyrdHtCNw3nM4tosk5ORqzqsvoDPVvgxoL7/u/HN5NyezzlJoKMJF4dxQoldAIlcQ/MIryDw97S660S3ch31n0jkem8Ut3YP4blss+UUGFkyrOXCrKfj7aDI//R1H/47+TB195aEnkQiEtHBGXaDjjiH2FUwQEbme0em01R6XyxVlxU2MRiNmc0Xf71IEQYJSqQRsL6h6ffX3NpXKoZbS2tz4aktqagqJiQk89lj5gOoRI25l0aI3ycvLw93dHaPRWCa/TCZDLpdjMBgB+O67NURERNKzZ+9an19EBOqgsN5///0kJdnqzc+dO5eTJ0/ywgsvABASEsIrr7zSsBKKNDmuvfuiOXMac0E+FoMBiaJiNHhjI0ilCFIpxuwsjNnZOLazpaASJBKcotoD0Ma9JefVF9BbDHZXvCol2CWAUJdgEgsvczD9KLeEDG6U6yhF7uWF1Wwmf/9eLHo9HsNHVNu/fUtPFHIJOQV68ooMnEtQY7Fayc7T4u1e+4dUQxPk44TZYiUrT4vVai2niD9/T1fkMimFGgNFWmNZqisRkRuRiRNvq/b4yy+/zsCBQwD45psvWbfu5yr7tm0bwbJlNotlfn4+99wzsdq5t2zZUTth60hi4iWACi4EYWEtsVqtJCYm4O7ehcjI9mzdupmhQ2/h4MH9FBcXER4eQVpaKuvW/cKXX37XJPKK3JjU+lWrX79+3H333QB4enry22+/8fvvv/O///2PzZs306rEB1Lk+sW55xUrXsGBfc0mR3H0WS69+BzpX62usB1edPIEUb8dxyvPZq04kH641vP3D7Bd596Ug02y3V585jQZa74ie/1aTAXVp+NSyqV0bOkFwJlLOWWlWa+VbAHhwe4seKQXz93TtYLVWC6T8s3WGOYs28POEynNJKGIiEhDUVhoSzHo7Fx+J8rFxbXkuM3VacqUuxEEgdtvH8WiRW/y2GNP4u8fwCefLGHy5DsJCAhsWsFFbihqbWH97bffGDx4MB4etio8giAQEREBQF5eHv/++y8TJkxoUCFFmhaJTIbU3QNznprCQwdxL/EbbWocWrdBolIh9/HBUlyM9KqbZcG+PRjORtPB6MDOHi5E58bRP7BPrebv3qIz6y5sJFObTVzeRcI9Wjf0JZTDqVNnHDt0wjEysoKrQ2V0C/fhaGwWx2Kz6RHhw4WUfKITchnUOaBR5bQHQRAI8nVGbzQTfSm3LBUXgN5oJjvftk2aV1RzkJmIyPXMhg2bqz0ul1/ZoXrooWncf/9DVfYVhKtKUru51Th3U/Pfl9MrL/q2dmdnZz777GtSU1NwcXHB1dWNI0cOERMTzWuvvUVSUgLvvvs2cXGxtG0bzksvvUZwcEgTX4XI9UqtLawvvfQSly9XHlmdnJzMSy+9VG+hRJofx3BbnlN9YkKzySBRKmn14VKCn3uxnLIKV4KvohIMSE1WXOVOtZ5fJVPRo0VXAPamHqy3vDUhCAJBc+fhOWo0EoUCi9FYbf/ObbyQSgRSs4tp4ekIwLlEm2vAtYDRZOGFlfv4ZP1pEtOvFHmQSQVik/IAGNZNtKiI3NioVA7V/lztqiSXy6vtW+r/Cbb7RU1zNxUuLrbsH6WW1lKKSoq7lFpaS+UODAzC1dUNk8nE0qUfMHPmXFQqFQsWvEabNm357bfNtGrVmrfeeq3JrkHk+qfWCmt1W6d6vb5WfoQi1y6u/QcBYNFqMWurDypoTCRKJabCAgoPHyrX7hgZhdvQ4RTdfStmKWTr6rZVXuoWcCLzNEXGpkl0r09JIfmjxWR+t6bafo4qOe1CbTsZOfk6FHIJhRojKddIQn65TEK7UA+83WwZA0qRSiRl6a3ik/OxWK4NBVtERKRuhIbafFcTEi6Va09IuIQgCISGhlU6bv36X3Bzc2f48BEUFxcRExPNhAmTcXJyZtKkO4iOPoNGc23cz0SufexyCUhNTSUl5YovWnR0NHp9+XQ2Op2OX375BX//5innKdKwOERGInV3x5yXhy4+DqcOnZpFDotez6Xnn8FqNKIMDkHhZ6tjL0gktLjvAVLST0H0YaJzz2MymWqdLiXEJYhg5wAuF6VyKO0ow0IGNcZllMOi16OJPguCgMett6Gsxq+rW7gPZy/lcjwum4hgD05fzCE6IZdg38bLalAbHhgVgYNShuQ/W4X92vuRnafj660xhAW4EuRzbcgrIiJSewICAgkNDeOff7YxePDQsvbt2/8kMrI97u7uFcao1Wq++eZLli5dVa5dp7NlPtBqa5/dReTmxq6n+/r161m+fDmCICAIAm+++WaFPqWWVzFLwI2BRCLBqUNHCvbsRhMd3WwKq0SpxCE8AnNhIeaiQsCv3PFAlS9tE3Vkeso4mHGM/oG1S/skCAL9A3vz0/kN7E09xNDggXannqorDq1a4dytO0XHjpKzYT0BM2dV2bdrW2++//M8l9IKGNcvrERhVTOq17Xh9+WkkmOxWDl1MQeZVCgrJTu0WxD7z2aQX2wgOatIVFhFRK4RdDod+/fbqu6lp6dRXFzMjh22ilVdunTHw8ODd95ZwNatf7Bz5xVXqWnTZvD66y8REBBEz5692bNnJ4cPH+DDDz+p9Dyffbac4cNH0qZNWwCcnJyJiIhk9epV3HPP/fzww7dERkbh6Fh7dy6RmxO7FNbRo0fTtm1brFYrc+fOZd68eYSGhpbro1AoaNu2LUFBQQ0u5JYtW9i4cSNnz54lPz+f4OBg7rnnHu6+++5yOeV27tzJkiVLiI+Px8/Pj6lTp3Lfffc1uDw3C46R7SnYs5vi0yfxufPuZpMj4Kk5SOSVp0ayrP2d2w4UcCzCgZOhp2utsAL0aNGV8+p4+vh1x4q1rIJWY+I1YTJFx49RdPwo2ovxOLSqPODL3VlJ60A3LqTkI5EITBsTSWSJm8C1wt9Hk/m/v+NoHeBaprCCLfXVhZR8W8WrqGYUUEREpAy1OpdXX32xXFvp78uWrcLDowcWi6VCEaBhw25Br9fx7bdf8dNP3xMYGMybb75Dr14Vg11jYs6xZ88ufvxx7X/Os4D33nubl19+jjZt2vLqqwsa+OpEbmTsUlhbt25N69a2B+o777zDkCFDyrIENAVff/01AQEBPP/883h5eXHw4EEWLlzI5cuXy3LAHj9+nCeffJLx48fz4osvcuzYMd5++20UCgV33HFHk8l6I6FqaUtRZkhLQ5+WgtK/eQJoJHI5Fp2O4jOncGgbjszNveyYS68+FB7YT+QlHevyU+s0v4NMxfQO9zeQtPahDAjAtW9/CvbtIXv9WoKeeb5Ky263cFuGgNjLeYwf0LVJ5bSHXpG+/LE/gZYBrpjMFmRSCVarldMXcwGIT60+hZeIiEjT4e8fwJ49R6rt88orb/DKK29UaB89eiyjR4+t8Rzt2kWyadP2Cu1hYS1ZufJLu2UVEbmaWqe1mjixYiLjtLQ04uLi6NixY6MosqtWrcLT84rlpk+fPmg0Gn744QeefvppFAoFn376KVFRUSxatKisT1paGkuXLmXy5Ml1qu5xs6Pw9UWQy7EajeT/+y++9zSftTpl2RK0sefxvfd+3IfdUtbu1KEjxU5ynIqNeMdnQR3z/5stZv5K2snhjOPM6/YEjnLHBpK8arzGT6Dw0AG0MefQRJ/FqX2HSvt1C/fmlx0XOJ+Ud00m4ndzVvLhU/2RXvUdEwQBhdz2+7USJCYiIiIicv1Say1uyZIlZUohwL59+xg1ahSPPfYYt956K3FxDV/O82pltZTIyEj0ej15eXkYDAYOHDjAmDFjyvUZN24cWVlZREdHN7hMNwsKf1vOz+KSetDNhVPnLsh9WyDIyitrgkRCTkebP2f7C1pMpqrLHlaHRJBwNPMkacUZHM44UV9x7ULu5Y3bEFsAQ/b6tVVm4PD1cCTIxxmL1crOEyms+O0My9aeahIZ7UUqkZCYXsgP22MxGG1bia0D3QAo0hrR6Or2dxEREREREYE6WFi3bdvGww8/XPb7xx9/TEREBDNmzGD58uWsXLmSjz76qEGFrIyjR4/i7u6Ol5cXly5dwmg0Vqiy1aaNrZZ5fHw8HTpUbr2yF6n05rTQunTrhj4pEWNmJjJZ+TUoXZOmWBufUaPwue22SrfNO465G/XBhQRnGvn7r68YM3ZGnc4xrvVIdCYd3f06I6vHNdVmXXxvH0/Bnt3oExPQnjiKa8/KfXB7tPMhOauImCQ1Zy+pkQgCRrMFB2Wtv8KNgsVq5dMNp8nO19Em0I3+nfyJCHZnz6k0ANLVGsKD3Zv0M3O9Ia5N1TT32lgsje/XXhdKb4eCANdIeuZrBnFtqqY51kYqFSroELWl1k+7jIwMQkJsFi21Ws3p06f5/PPPGThwIHq9nvfee69eAtnD6dOnWb9+PTNnzkQqlZKfbysL5+rqWq5f6e+lx+uDq2vz129vDpwmjCH7tw1gsSBJvoRbx4qKf1OtjcVoJP/0GaSOjri2iyhr9/DoxtedfDDnF/CPJI52xRfoEdS51vMP87gSPGAym5BJ66cM2rUuHk5ox4/j8s+/kvPbekKGD0KoJJfxsF6h/Lb7EnGX82nh6UhGrobkXC29ovwqmbR5GDewNfEpeUS08sLDw4lOES3gj3MAZBfq6e1xJRr4Zv0+2YO4NlXTXGuj00nJzpY0yEO3MRBfcqpGXJuqaYq1sVgEJBIJbm6OqOyo8FgdtX4iW63Wsq3LY8eOIZVK6dmzJwC+vr6o1Y1b6zwrK4vZs2fTsWNHHn300XLHqgpaaYg0RQUFWsxmS73nuf5QIHFwwKLVcnnzn1iCWpYdkUoluLo6NNnaZP3+G1kb1uPStRvBc+aWOzZ65kJe3rMQk0nL+3tW8lrPuQR6Btf6HLG58ayL3USgiz8Ptr+zTnLWdl0ch9yCcu9+3IYOQ60urlRhdVNJ8XV3IDNPi4+bioxcDQdPp9LW36VOMjYGQ7v4M7SLLQ+zWl2Mi1KCRACLFU6ez6RfVIsm/8xcT4hrUzXNvTYGg74kct6KyXTt/G0EwbY2ZrNFtCL+B3FtqqYp18ZstmKxWMjP16DVmiscd3V1sFtxrrXCGhISwo4dO+jbty+bN2+mY8eOZVpzZmZmBStnQ1JYWMijjz6KSqVi5cqVyEtSHbm52Xzl/mtJLSiwRSc3hExms+WaulE1JcqQULTnYyg+d67SNWiqtXHs1AXpP38j9fKucD6pRMHsbjN4b99HDDtcyKndb+M5fylymaKK2SrHYoGEgsukFqUzsfVYHGR1fyO0e13kSkJefwtBEDBZrGA2IVQSJNg13Js/D11GX+IjevZi7jX3mVQX6vn3eAoKuYQxfcMY0TOEPw8lkZ2vKyfrzfx9qglxbaqmudbGbL42NZ5SZUNUyCoirk3VNMfaNMTLXq3twXfddRfffvstvXv3ZvPmzdx55xUr1LFjx8r8RhsavV7PE088QXZ2NqtXry6XjSAkJAS5XM7FixfLjblw4QJAWUoukbrh0sPmV2nKy8NirviG1FQogoJptXgJvnffW+nxQGd/Jrj2IjxRR2iylj++qH2d6tZuYfg5+mKwGDmScby+ItuNIAhoL8aT/P475P21rdI+3cJ9ALicWYQApGQXk1+kr7Rvc3E5s5CN+xLYejAJo8nMiB5BPHxbO+4bEd7coomIiIiIXMfUWmG99957+fDDDxk3bhzvvvtuuTRXer2+0rRX9cVkMjFnzhxiYmJYvXo1gYHl84EqFAr69OnDli1byrVv2rQJHx8foqLErOX1wbVfP5ArwGrFkJLcbHKUunZo4y9QcPBApX2G9bmD2GE2/1bXyzl8deq7Wp+jf2BvAPakHKwycr8xMKQko42LRb19G9ZKXgxaB7rh5qRAZzDj42Hz5YtObFwXnNrSoaUXvSJ9eWBUBIIg4OqkINjXmdzCa0uxFhERERG5vqhTVMmYMWMqpJACeOutt+otUGUsWLCAHTt28Nxzz6HT6Thx4kTZsTZt2uDs7MzMmTO5//77mT9/PuPGjePYsWP8+uuvLFiwQMzBWk8kShVOkZEUnzqJJvosqpDQmgc1ErpLF7n8zttIHBxw6d4DQVbxIzzh7pdYaXiO6ACwZJ+mXcoh+tWiAlYvv278fmEzyUWpJBUmE+pae1/YuuDabwDGrCzchgyr1I9VIgh0bevNvydSUcptx6MTcunb/toJvJJIBGaMvxKYl5heyII1R5BKBJ65uwsdWnk1o3QiIiIiItcr14Umt2ePre7x4sWLueuuu8r9nD17FoCuXbuyYsUKTp8+zbRp01i3bh3z588Xq1w1EI6RNit18enmzf+patkKuZ8fTp06Y9Zoquz3wN2vg0QKViunN35LRu5lu8/hLHeii29HAPamHqq3zPYiSKV4T5qC3NMTY1YW5sLCCn1K3QJyC3TcPbwtY/qGNZl8tWHHsWRe/+oQEonNwd9ssXIqPqe5xRIRuenZvHkjAwb0qPCzcuUnNY7dsmUT9947mWHD+vHAA3fyzz9/lTtuMplYsuR9Ro8ext13T2T//r0V5pg163F++eXHBrsekZuHWltYjUYjX3zxBZs2bSI1NRW9vvxWnyAIDZ6o/59//rGr3+DBgxk8uI6ljkSqRVliVdWej8Gs0SB1bPxKUJUhSCSEvfVOjZkfnBXOzOw8jbNffEjHCzqOZLzNyJeXlwXq1cSAgN4cyTjBkYzjTGozBlU9gq9qi/qvbWT9+jPuQ4fhe3f56mLtQj1wUMoo1plo6e+Cn2fz/B1q4mR8Dpczi9h/NgM/T0f0BjNhftdORgMRkZudDz/8BCcn57LffXx8qu2/Y8dfLFz4BvffP5Vevfqwa9e/vP76Szg7O9Orly0l4KZNv7Nnzy7mz3+TI0cO8cYbL/Prr//D1dUWGP3339tRq9VMmlS3DCwiNze1Vlg/+ugj1qxZw6BBg7jllltQKGoXhS1yfaJqG16WZTh/z248R45qVnn0KSkUnzqJx6hbK42oB2jn1Zb4Xr0wX9xF28t6fl79PPc/scSu+du4t8LX0ZtMTTZHM06W+bU2BYqAQDCbyf93Bx4jRiH38i47JpNK6NzGiwNnMzgWm0XbIPcmk6s23NorhA4tPenbwY87hrRukNRyIiIiDUdERCTu7u5291+9ehVDh97CjBlPAdCtWw+SkhJYvXpVmcJ65MhBJk++k/79B9K7d182bfqds2dP07fvAPR6HStWLOXFF19FVokrl4hITdT6U7NlyxZmzpzJU0891RjyiFyjSCQSZJ5emHKyKTp2pHkVVrOZy+++jUWrxaFNWxzatq2y65hhj/DNpRj67s+kxzE127Z/xcgRj9R4CkEQ6B/Qmw0X/mBv6qEmVVidotrj0C4Sbcw5cn7/Db9Hppc73q2tDwfOZnDoXAYanQmFTMp9I6+tKPx2oR60C7Vl8tAZTPx7PJWUrCKmjRMDIEVErjdSU1NITEzgscdmlmsfMeJWFi16k7y8PNzd3TEajSiVSgBkMhlyuRyDwQjAd9+tISIikp49m+5eKnJjUWsf1vz8fHr06NEYsohc4zi2iwRAfzmpWeUQZDKcu/fAqVNnsCPh8L0PLiSmjRMSK7TYsJvY+KN2nae3X3ekghSdWY/GWLW/bGPgPcnme12wfy/61JRyxzq28kIuk6AuNLD7VBr7z6ZjsVx7yQaTM4v44KfjLP31JOt2xrP3TDpp2cXNLZaISIOi02nR6bRlGUV0Oh06nRZzSaYPg8GATqfFZDIBNrc6nU6LwWAAwGw2o9Npy9zrLBZL2Zw1naM+PPDAnQwa1Is77hjPd999XSZvZSQmXgIgLKxlufawsJZYrVYSExMAiIxsz9atm8nNzWHLlk0UFxcRHh5BWloq69b9wlNPza2XzCI3N7VWWHv27ElMTExjyCJyjeM20OYfbNXrMeQ0bwBNi4ceIXD20zi0qjnHrlwuZ/jsRWR6KZBaYOPBHygyFNU4zkXhzCu9nubV3s/gKG9aX1GHVq1w7todrFZyNqwvd0ypkNKhpScAMqmARm8iMaNigFZzo1JIOZegJvZyPuYShTo64dpKwyUiUl8mTryNiRNvKytcM2fODCZOvI2zZ08DsHjxIiZOvI0tWzYC8PPPPzBx4m188cUKAPbt283Eibfx6qsvAHD5ciITJ97GQw/dU+M56oKXlzfTpj3O/Plv8sEHy+jbtx9ffLGSpUs/qHJMYUkAqLOzc7l2FxfXkuM2uaZMuRtBELj99lEsWvQmjz32JP7+AXzyyRImT76TgIDyKSlFRGpDrRXW+fPns3btWrZt21b2hihyc+DQpg2UpFvK/9e+QLjGQhAEjDnZqP/ahiE9rcb+To5uBDwxi19GeXDRT8bbBz+q1qJQSgsnXyxWCycyT6M3N+3n3WviJBAEio4fRfufohil2QJkJRbm6ITcJpXNHrzdHZh6Wzvem9EXZweb91FMkqiwiog0J7179+Xhhx+ld+++9OrVh3nzXuCuu+7j99/Xk52dXe3Y//qiX8lTbWt3dnbms8++5ueff+OPP/7ivvse4siRQ8TERHP//VNJSkrgySenM2LEIJ58cjqXm3m3TuT6QrDWMjN6165dMZlMmEwmBEEoK8taNqEgcPSofVuu1xNqdbFYLhFIeO0VDKkpKIKCaPP2Ijw8nJptbVKWL6X4xHE8x43He7x9BSt2JO1m7YWN+OQaaV3swAMPLapxzIdHV3AxP4H7291B34CeNfaXySQNti7pX62mYN8eHNpFEvzsC2XtRVojc5ftwVLy9Y0M9eC5e7rW61yNyVtrDnMpvRBfDwe+nD9S/D5VQkN+bm40mnttjEYDOTlpeHn5I5eXDzQu3ZpXKlUIgoBOpwOsyOUKpFIpBoMBi8WMTCZHJpNhNBoxm01IJFIUCgVmsxmj0YAgSFAqlVgsFgwGm3uASuVQ7TlUKgdkMkm91+TcubM8+uhDLF68lL59+1c4vn//Hp57bi4//LCW0NCwCuM+/XQ1nTt3qTDOZDLx8MP3MnXqowwfPoLp0x8kKqo9jz8+k5UrPyE29jyff76mXrJXR0OszY1KU61Ndd8dAE9PJ6R2uPZBHYKuRo0aJUb83sQ4duyEITUFY3p6c4uCS/ceWDQaFH7+do8ZGjKQ09G7uWV7LBKLml98PubO2+ZWO6ajVyRZ2mws1qa/8XmNn0DhoQNoY85RHH0Wp6j2ADg7yIkIcedcSaWruOQ89EZzWUGBa4kf/4olId22pagWK16J3GCUKpVXfi9vxPlvJh25XF4uvZ5UKkUqvTKHRCKpZM7qz1FfarJbhYbafFcTEi6VU1gTEi4hCEK5tqtZv/4X3NzcGT58BMXFRcTERPPyy6/h5OTMpEl38OCDd6PRFOPo6NRQlyJyA1NrhfXdd99tDDlErhM8hg0n788tWE0mjOpc8Gi+G41r3/64VmINqIknhj/HliOzaJego+3mU1zseYFWPm2q7D8kuD/DQwYhlTS9Mij38sZtyFDy/tpO7qb/lSmsYHMLOJeoRioRMJmtXEjOp32Jb+u1hEImpfRxaDRZKNKIrkQiItcSf/+9HalUSnh4RKXHAwICCQ0N459/tjF48NCy9u3b/yQysn2l6bHUajXffPMlS5euKtdusw6DVqtruAsQuSm4LipdiVw7yL28UZZEihY3cIGIumAuKiJ/z26KjtvvhiKXy+k981Uut1DwZz9XPjm7hgJ91UFLCqkCiSDhQt4lDqUfawixa4XnbeNwHzEK/xnlU8qU+rGWBTQlXnt+rADDuwfx8v3dUMhtt5uEtIJmlkhE5OZl3ryn+OGHb9i/fw/79+9h8eJF/PLLj0yefCdeJTmf33lnAYMHl08/NW3aDP755y8+++xTjh07wrJlH3L48AGmT59R6Xk++2w5w4ePpE0bW9pBJydnIiIiWb16FYcPH+CLL1YQGRklWldF7MYuC2tp+VN7ad++fc2dRK5bnKLao0+4RNHp0zC2eQsIFB46QOaP36Nq3cYWVW8nLTwCyX/mBdaf+AwsBt7a8RaLhi+sshJWXN5Flh7/DAeZA118OqKQ2lcxqyGQubrie5ctYtiQkY7c2wdBKsXDRUlLf1cupRXQuY0XvSNbNJlMtcHDRYmHi5LwIHfOXMrlckYhgZ4ONQ8UERFpcEJCwti48XeysjKwWq0EB4cwe/YzTJlyV1kfi8VSISh12LBb0Ot1fPvtV/z00/cEBgbz5pvvlBUNuJqYmHPs2bOLH39cW6791VcX8N57b/Pyy8/Rpk1bXn11QeNcpMgNiV0K6+TJk+3yW7VarQiCwLlz5+otmMi1iyIgAICCgwewWJrXod2pa3eUe3bj1LFT2efPXsI9W9PJpz3ZZ49z254Cfst4izseqvwG2sa9JV4qD3J0ak5knaaXX7eGugS7yVr7C+ptW2nx4FTcBgwCoHuED5fSCjCZrYS0uHZLnyZlFHK+JENAbFIefSJ9m1kiEZGbk7lzn62xzyuvvMErr7xRoX306LGMHj22xvHt2kWyadP2Cu1hYS1ZufJLu+QUEfkvdims77zzTmPLIXId4dips+0/Vit5R48htIlsNlnkHh6EvvZmncc/3vEhvt9zEiedhQ57kzgQ8Tt9+oyv0E8iSOgX0IuNF/9kT8rBZlFYZa6uYLGgu3SpTGHtFu7D2n/jiUlUo9EZcVQ1neW3Nvh7OdlK+2LlTHw2cG1V5hIRERERubaxS2GdONG+lEEiNwcyRyckTk5YiovJ+HsHfs2osAJY9HqKz5zCmJmJ5+gxtR5/z2OL+XvRbMISi1H88DvnWgQT2bKiQtrHvwd/XNpOfP4l0osz8HNq2i14t6HDULVug0PrKwFifp6OBHg7kZpdzGf/O0t4sDtj+oY1qVz2IJdJmD42kpW/nUWjN9YYlSwiIiIiInI1YtCVSJ1QtWwFQO7BQ+Rs2dKsspjUatJWfkr2ul8x5efVerxUKqXH7NfJcZPirLWQ8flKijUVA4PclW508LIp53tTD9VX7FojkStwaN0Gi05H7pY/MGttuRlLg69OX8xl96maiyg0B1arFa3ehABYLPD2N0fQ6IzNLZaIiIiIyHWCqLCK1AnviZNtW7wWCxk//x+XXnoeQzPlZlX4+eHSuw9ug4cic3PHrNGgjb9Qqzk83XwxPTAZvVwgIMvI5h8qd4PpH9ALgIPpRzGam0fhSlm2hOx1v6LethWA7iUKK0CmWkt2Xv1qjDc0GWoNH/58gjVbziOTSSjSGolLzuePfQlsP3y5ucUTEREREbkOEBVWkTqhCg2jzQcf4RASDIAxK5OEV18mf9+eZtnu9Zv+OD533wtA9oa1XH53ITl/bKzVHAO73EbG+P6cauvArjATy4+vrtAnyisCd6UbxUYNJ7PONIjstcV92HAA1Nv+xFRYQEgLZ7xcryQSj068NsqfmswW/tifwGtfHiI6QY1cJuH2/qGMH9SKjq08+ftYCv/3dxyPvr+DMxdzmltcEREREZFrGFFhFakzCi8vun3yMX5TH0aQycBqIeOr1aR8tBhDRkaTyiIIAhK5HKvFgtVoBKsVh1atATAVFNitRN9y63QShnfAIhU4l3ueXw5/X+64RJDQz99WnrU53AIAnLv1QBkahlWvI/ePTQiCUOYWAJRVv2pOLqTk8+aaw6zbeRGjyUJUmAdvTevF+IGtmT6+I09N7oRvSWors8XKR7+c5P0fj1VIpSMiIiIiIgKiwirSAHgOGUrrpcvxmjgZQS5Hcy6ahFdfIvmjxVj0TVvNRJBI8Js6jdAFi3CMjMKi15O08E1Sly/FVGBfwvrZXR9FbrQwZk8Brb/7h7jk8pbUvgE9ERCIzYsnQ5PVGJdRLYJEgvekKQDk//sPxpxsuoV7lx2PTsjF0kxBTVarlR+2x/LOd0dJySrG2UHOo2OjeOauLvh6OJb1c1DKWPBIb/pEXQlci0nK4/EPdrL9cFJziC4iIiIicg0jKqwiDYJEqcJrzDhC33gbVavWYLGgiT5L/JxZ5O36t8nlUZbkitXGxWLKy0OffBlJSU3vmqytCqmCWZ2m45VnwkVj4fKqZWh0RWXHPVUeDA8ZxH3tpuCudGu8i6gGx6j2OLSLxGoykfO/32kb5I6zgy3pR6HGSEpWcbPIJQgCUomAFejf0Y9Fj/Whbwe/KvPjPnZ7ez6e3R9fD5tLg8UK//f3BRZ+dwSTuXlz/IqIiIiIXDuICqtIg6Jo0YKgF1/BbfAQQMBqMpL57RoSXnsFQ07T+yk6dehI6OsL8J/+OBKVCs25aJIWLkCXlFjtuNb+7TA9MBGDTMAkwIcHPi53fGKbMfQL6IVSqmgWn11BEMqsrAX79mBMT6Vr26vcAhKarkxrTr6Os5eunG/CwJa8cG9Xpo2Jwtmh5rywro5K3n28H3cPb0OpXhufUsBzK/axce+lxhJbREREROQ6QlRYRRociURCiwemEvbWIuQ+topGhtQUEl58lsxffmry6ljKgEAc2oZjtVrJXr8WfcIl8nfvrHFc/25jOX5HN/432I10SwG/nv+93PETmaf58OinHM863ViiV4tDq9Y4de0GVis5v62ne4RNYVXKJbQOanzLr8ViZdvhy8xffZBVv5+hoNgAgEohIyLEo9bzjewZwufPDmZIlwAclTLyiw1s2H2JJz/cSW5+07qWiIiIiIhcW4gKq0ijofD3p+U77+N9x10gldoqY23bSuKrL2HMbXprqyAIBMycjdvgIXhPtFknczb+TvHpU1WOeWD4LFp7tEawWDH88SfHj18pN3i5MIWL+Ynsa6bgKwDvCbb0YkXHjtLKkodKIUVvbPwXgsT0Qt7+9gg//R2H3mjG39sJvbH+AVNSqZQHb23HKw92x1Fpc3HQGc0s+PYwe06liUFZIiL1JDn5MosXL2Lq1HsZPLg3DzxwZ6X99u/fw8MP38uwYf24664JrF//q13zm0wmVq1azvjxoxg+vD+zZj3OhQtx5frk5ubwzDOzGTlyME88MY3k5PLp7QoK8hk7dgTnz8fU7SJFbkhEhVWk0fEcNZpWS5ahatsWAGNGBgmvvox6+59Ym9jaKnN3p8UDU5E6OqKNv0DO7xtIWfoR+pTkKsfM6jqdgWcN9IzWYFrzf8Qk2xTcfgG9uL3VrTwQWfkNvylQBgbi2rcfAIa4GDq19gLg2PnGCQbTG8z8/E8cb31zhIT0QhyUMh68NYIX7+uGj7tDg53H38uJ5U8Ponu4D25OcgqKjXy1+RyPf7CT3SdSG+w8IiI3G5cuxbN//16CgoIIC2tZaZ8zZ07x4ovPEB7ejg8+WMbo0WP5+OPFbNz4W43zL1v2IevX/8q0aTN4990PkUqlzJ37BDk52WV9li79ELPZxNtvv4dCoWDhwjfKzfH55ysZOHAIERHt6nOpIjcYglWskWgXanUxJpMYBHI1MpkEDw+nWq2NJi6O7HW/oCt545Y4O+N7z/249u7TmKJWikWnI+f3DZh1WvweegSLTkfh0SO49u2HICn/LpeccZG0RW/jVmwh0V/BoNeWoZRfyX1qNBuRS23+mnVZl/pgzM3BXFiIKjSMQ+cyWPX7WZxUMu4a1oYBnQIa7DzRCbl8vTmGnALb9nyvSF/uGd4WN2el3XPUZW2MJjNfbY7hYPSVVGnd2nozY3wHZLIb5527qT831xPNvTZGo4GcnDS8vPyRyxVNfv7qkMkktVoTi8WCpOT+tnDhG8TERPPdd7+U6/PMM7MpKMjniy++KWt7772F7Nu3mw0bNpeN/y9ZWZlMmTKOOXOeZdKkOwDQaIq5447bGTt2Ak88MQuAMWOG88EHy4iMbM/Zs2d4/PGpbN++GwcHBy5ciGPOnBl8//1aPDxq71p0NbVdm5uJplqbmr47np5OSKX23cdvnLu9yHWBY9u2BD//Er4PPIQgl2MpKiL9i1UkvvWG3WmnGgqJSoXPXffQ4sGHAcj5fQMZX68m/csvKvQNatGK9ClDMEohNM3AxpUvAVBgKOTzU9/wxoH3MVuaZ7ta7umFKjQMs0ZDWNJJJECxzsRfR6u2GtcFrd5MToEOL1cVc+/oxIzxHWqlrNYVuUzK47e357Y+wUhKgrKOxWXz2Af/8sP22EY/v4hIdeh02kp/St1XLBZLufZSTCZTFWOv+GsbDIaydoPBcNU5deXmqg1VKZtXn/PYscPccsvIcu0jR95KTk42sbHnqxx76NABzGZzubGOjk707z+I/fv3lLUZjSaUStu9Q6VSlbTZKgd+/PFipk59tN7KqsiNh6y5BRC5+RAkEtwHD0XVshWpnyzFpM5Fn5jAxWfn4jn2drxvn9C08pSEpsu8vRGUSlz79gXAkJGOzNMTSclb4biBD7I29TKdtsfR6ZSades/YMKEp7lYkEihoYjTOefo4tOhSWUvxWoykfjGq5hycxjS4Tb+0XlzOaMIrd6Eg7JuX3OL1cr5pDwiQ20Pju4RPjx8Wzt6tWuBUiFtSPHtYsqQtkwY1JqvNp3jQIm19e+jyaRkFTFnSudmkUlEZOLE2yptf++9JXTq1IW0tFSmT38AsPlob9r0FwBbtmxkxYplFcaFhITy2WdrAPjqq8/5/fd1AIwfP5kZM54CYM6cGSQlJbJly46GvhxSUpIxGo2EhpZ3FwgLawVAYuIl2rWLrHRsYuIlPD29cHUtH/QZFtaSbdu2lFl3IyOjWL9+LY899iTr1/9CYGAQrq6u/PXXn+Tn5zGxJMZARORqRAurSLOhCgml1eKP8Lx9PEgkYLGQ+7/fuPj8PHSXmz55vMfwEbR670OcOnTCYjCQsnQJiW+8hj41pazPlLte4WykGzq5QLzmMvvSDtO3rPLVwSaXuRRBJsO1X38U/gG0be0HgBU4fzmvTvOlZBfz7g/HWPx/x8ulyBrYKaBZFUOZRMJjt7fn8dujkEltLxoxSXm8sGofX26Kbja5RERuFAoLbTtdzs4u5dpdXGy/F1SzE1ZYWIizs3OFdhcXV0wmE1qtBoCZM+ewe/cObrttGH//2lDq/QAAKutJREFUvY3nnnsZnU7HihXLmDv3OWQy0ZYmUhHxUyHS7HjfPhH3wcNIWbYEfWICptxckt58DY9bx+A9aXIFf9LGRFpyszVmZGDR60EAmYcnABaDAYlCwagnF/LW329S4CiQdH4DT3SayjbgXE4sOVo1LVy8mkzeq/EcMxav2yfgqTPBWdv227HzmXRp413DyCsYTWY27ktky4FEzBYrSrmUvCJDzQObmN5RfvSO8mPH8WT+2JdIbqGevWfSORCdwdN3dCaqpWdziyhyk7Bhw+ZK20v99fz9AyrtM3r0OEaMuLWSkVeKbDzyyGNMnToNAInkyovi0qWrsL2SNh5VFfuoornacaWhMqXHwsPbsW7dH6SmJtOihT9KpZLPP19BVFR7unfvyd69u1m+fAm5uTn07z+IZ599CUdHxwrzitxciBZWkWsCmZsboa++gd+0xxBKKlKpt/5B8uJ3y1k4mwplcDBhby0i8Km5SB0c0MbFcemFZyk4sA9HB2eeHDQXAL8sA7GrP6GtW0usWNmf1nwpriRyBQgCQvRJHsz8B6nFzOmL9hcQOJeo5rUvD7FpXwJmi5Uubbx5e3pv+nbwa0Sp68fQrkG8OrUnro62gDezxcoHP5/gja8OYRBTYIk0ASqVQ6U/UqlNwZRIJOXaS5HJZFWMvRLMqVAoytoVCsVV51SVm6shcXFxBa5YWkspLCwsd7zysS5l/a6mqKiw7HpLkclkhISEoVQqSU1NYcOGtTz11NOo1bm88cbLPPzwY/z0028kJSXyzTdfNsSliVzniAqryDWFa99+tP54OZ5jxiEolWjjYkl841Uuv/8OJk3TlhuVOjqiCgsDQP33NsyFBWhibHkBg10DGdNiEON35NH+gga//bbgn/1pR5ot+ArAajKS9fOPBBQk063gPPnFBvKL9NWOKdIa+eqPcyz+v+NkqLW4OSt4ckIHZk3uiJebqtqx1wJuTgo+nj2Q2/uFldmmkjKLePKDnSSmN20gn4jI9U5gYBByuZzExPJV5hISLgJU8G29mtDQlqjVuRQU5P9n7CVCQkKrDPj65JOPmDLlLvz8/Dl79jQKhYKRI2/Fw8OD0aPHcPhw87lbiVw7iAqryDWHRKHAe+JkwhYsxKlTZ7BY0Mae5+LTs8nd9mezyOQ//XG877gLnym2nKvZ69fSJxFi+oUC0OmUGi+dlDx9Pmeymy/ZtUSuwGvcBAD65p5GYTFwNLb6nKw6vYlDMRkIwNCugSyc3oce7Xyr3BK8VpkwqBXL5w3E39O2dWixwoJvjvDWmkNk59UtolpE5GZDoVDQrVtP/vnnr3Ltf/31J15e3oSHR1Q5tlevPkgkEv7550qBFY1Gw969u+jbd0ClYw4fPkBs7Hnuv/+hsjaj0VSWZUGrFb+7IjZuOIX10qVLTJs2jS5dutC3b1/efvvtcmlCRK4f5F7eBMyai/uIUTbHKbOZ7F/+j0svv4AhI71JZRFkMjxHjUbq7Iw+NYXcLX+QvX4tY3rdRULPMNYPdydHZbvB7klpXmuAa/8ByFv44WjR00sdTW5BRQtrZp4WY0kOPm93Bx4a1Y6XHujOA6MicFRdv67tDgo5Cx/rw8yJHQkPdMVqhUvpRTy/aj+//H2hucUTEWl2dDodO3b8xY4df5GenkZxcXHZ72q1GoCHH55OTEw07733NseOHeGbb75k48bfmD59Rjkr6V13TWDOnCfKfvfx8WX8+EmsXPkJGzf+xuHDB5g//3kA7rzzngqymEwmli79kKeemotSadvNad++IxaLmZUrP2Hv3t2sX/8rPXr0bMwlEblOuKEKBxQUFDB27FgCAgJ48sknyc3N5Z133mHgwIF88MEH9ZpbTOZdkaZM5m3IziJ16RIMaaVVjgTcBg/B574Haswr2NBYrVYK9+9Dl3AR33sfwKDTsPazFzjcTolKb0WnlLB00jtI9Ipm+8wUHjlE2qoV6AUZuwZPY+b9tlRdJrOFPw8l8b+9CYzpE8rtA6re3msMmvIzY7FYWLMlhj2nr7zc9Ir05fb+YQR4V4xkbm6aOzn+tUxzr82NVDggLS2VO+64vdJjy5atolu3HoCtNOtnn60gMfESPj6+3HXXfUyeXL6q35Qp4/Dz82f58s/L2oxGI6tXr2LLlk0UFRURFdWeOXOepW3b8Arn+/nnH9i7dzfLlq0q175nz06WL1+KWp1D374DeP75l3F0dLL7GksRCwdUzfVYOOCGUlg///xzVqxYwT///IOnpy1KeOPGjTz77LNs3ryZ1q1b13lu8SFSkeZ4iOT9u4Osn37AajIBIHFyIuj5l1EFBjbJ+Ssje/1acjdvItdFgqPeSpKfgs4vvkRLx1bN9pmxWizEv/k6lpTLHPGIYuLb80jNLuabrTEkZ9l8gTu19mLOlE5NuvXfHJ+ZyxmFfL4xmpTsKz7Q7ULceOauLmWBMdcCza2UXcs099rcSArrzYS4NlVzPSqsN5RLwK5du+jbt2+ZsgowatQoFAoFO3fubEbJRBoK9yFDaf3xchwiowCwFBdz+e03yN28qUyJbWocI6OQ+7Ygv1Mr5CYr4Ul6jn7xabPIUoogkeB/510AdFHHsPCT7Sz67ijJWcU4O8iZNiayyZXV5iK4hQtvTe/N03d2LmuLScpn7id7ORGb2YySiYiIiIjYyw1lYe3bty+TJ0/m2WefLdc+ZswYunTpwsKFC+s8d0GBFrNZfFO7GqlUgqurQ7OtTdGZM2T9/hvauJLynCXFB6pCkMmQlJQDtJrNWGrwbZY4OpYpdGatttq5kcmQKpXodRpkZttXqqYvllEKZqmAylB9T6ME5LVcXrMA0pJpBTtkaW4sAAJIrnVB/4OVq7NmipRiBQxyUBobbr6C++9k4Kjbm+VeYzDoycxMveYsrIJguw+bzRZunCd5wyCuTdU05dqUWlh9fQNQKCqW8nZ1dbDbwnr9RldUQkFBAa6uFXPEubq6kp+fX8kI+3F1bZycdzcCzbU2HgN7EzSgF1k7dnLpqzWYKsn/dzVWkwlzLaywFo3GfmFK5r76C1WTIqMwA+aa7xaKOjyfZf+Z9lpXqqRw7WvVlXCtr2tzIQCqBlJWS+fLT01utnuNTiclO1uCVCogk117G5P2PvBvRsS1qZqmWBuLRUAikeDm5lgux3BduKEU1qqwWq313voULawVaW4Laynyrj1p82FntBfisBiqrsokUamQlbzQWAwGTHl51c/r5YVQ4uNozM2t1uVA4uCArKR0oUWn48SBjRSYTbRw9sHNyYO0vFS0EjMSkxm5zozRSYHe2xWLUoEqMR2hoAijTILK2RV3iSMWrZYiiQmztxtyByfMWTkU6YuQOzriqHTGWlhEoaEIpUyJg9wBSbGWfF0BZgcFHoEtcVA4kFOUjaZAjbLIhEprQYIUra8rVqkUITsbq0aDxk2F0cUJpyIjisJiMIPByw1HqQPKvEI0+kJQqVA6uSGxCqQ6aLEAKpOAY2Y+RokFo4MSZ7kzKqsMo1FLoVWH3AJypSMyk4UCRylWmQwnrRlpQSE6BwGrozMqjQmJRotWIUET6INMKkWWlYtZU4TUKuDk5IVMIkWrK8Js0qOQOyA1mtGZdBR4qJA5OOFoloJWQ6HMjNRswUljwcEgYHSQondyQGq1IssvpFgwYXRU4CR1RJlXhF4Cxb4uFOdakRcWIDMbMbnIUMod0QgyMGuwWkzIDRYkOpCaDcjkAhJHZwSTM3qTjiJnPWaVHKXeilJjROOooFghR6HR4JpXhEKQYFbJsViUyM0GFFILGj8PtDigLyjGpeD/27vzuKjq/X/gr4FZWBRGxAVQEbEZZBG1rwgKuOWWgIrlpdJMFHEFJczMq5mKZKkY4pKC2y0tvXIpCbzxy5AssYdXr+GCyhKoJLIzDDDDzHx+f3A5OTIUKcrAvJ+Pxzx8zOd85pzPeeEw7zmccz7lUJsLYGRsAk0DHzyVEmpTQK0GhHX1MGZqGHXhQ2NqCtSZwqiuDhq+HCqeEUQqU5g0aKAwMUKFpRBGKhUEtQpoeCrITUUwlTfAtF4JEQOMupijnt8FKkUDTOTl4IsAnpUYtfxuUMiqUMuvg1ClgbC2ASKFEiqRCKyrGUzr+VBqlDAybkC9hQDGSiH4dWqYKGtR10UIBTOGaY0a0DRAYWoMtRFgplDBiA8oe3ZDqYkZRMWlsKyohogP8My7gDErqOprwYxrwHgq8HimYOChjq+C0kwASxmgUWmg5KuhFPFhVg+YKhtgYtMHr4cvb7ffNUqlAhqNBmo106tzIukoYssom5Y9z2zUagaNRoOqqlrU1TW/R7nBHmG1sLDQOc+xTCZ7qguuAECt1ujVLyp9ohfZGPEhkgxqdXdjAII+9q3v39Om1X1FfCO8/OJarQtE+v7RCzxaveoOr70vntFnlE3Lmo5qttfvGnUr/hLSHpqKDSrImqNsWtYe2bTFl71Odazc0dERubm5Wm1KpRKFhYVPXbASQgghhJD20akKVl9fX2RmZnI3PwaAtLQ0KJVKjB49uh1HRgghhBBCnlSnKliDgoLQtWtXLFmyBD/88AOSkpKwadMm+Pv70xFWQgghhJAOqtOdw3rkyBFs3rwZy5cvh4mJCfz8/Jrd5ooQQgghhHQcnapgBQAHBwckJCS09zAIIYQQvXP27P9DWloqbt3KRnV1Fezs+mD69FcwbVogN811VNQGpKYmN3vttm2x8PQc+YfrV6lU/5ua9fT/pmZ1RXh4JAYOfIHrU15ehqioD5CVdRWOjgOxdu0G9Onz+6Wp1dVVeP31V7B9+y5IpU5ttOeko+t0BSshhBBCdPvii8/Qu7cNliwJg5VVd1y+fAk7d36MoqL7WLo0nOtna2uH9es3a722f3+HP11/bOx2nDmTgmXLVsDGxgaff34UK1YsxpEjX6B7d2sAwCefbIdarcLmzVvx+edHEBW1AXv3/n6gaf/+vfDxGUPFKtFCBSshhBBiILZujUG3bt2458OG/R/q6mpx6tQJhIQshlDYOJOXSCSCq6vbX1p3SclDfPVVIsLDIxEQMAMA4OLihldfDcCJE8exePFyAMClSxexbVssBg1ygbl5F4SGvoW6ujqYmpoiJ+cOvv8+DZ999s822mPSWVDB2ko001XLKBvdKJeWUTYto2xa1p4zXVVU8GBkxNPLmZP+ypisrbs3a5NKnaBUKiCXy2Bq2gM8Hg883l/f10uXLkKtVmPixMnca7t27Qpvb19cuPAjli1rPILb0KCCqWnjDePNzBp/phqNGsbGRvjkk20IDl6oc5xPQh9/XvrieWSjVje+bywtTXXOdGVk1PpJnahgbSX6T98yykY3yqVllE3LKJuWtVc2jdvlgcdrnCXoUXV1da1ah0AgAJ/PR0NDA1QqFYyNjSEUCqFWq6BUtm4eWxMTE/B4PNTX14MxBlPTxmLvKSdyxNWrV2BhYQkrKytuXffv38OECb6or6+Ho+NABAeHYPTosX+4nl9/zYeVVXeIxZZa7Q4OA/Dvf6eCMQ2MjIzg7OyMxMSTWLRoKRITT6BPnz6wtLRAWtq/UVVViZkzX33qfWrSVuvpjJ5HNo3baPzy87TvXypYCSGEkCcUEDC5Vf2WLVuBadNm4Pjxz/CPfxyGv/90hIWtxPnzP2Dz5g2tWsfJk19BLBZj2bJQFBT8irS0c08x8kY3b95AcvJpzJ+/EMb/m4paKpXC2dkZDg6OqKmRITHxJFavfhtbtnyEceNeanFdMpkMXf83RfWjuna1gEqlQl1dLczNu2D58pWIiAhDYuJJdOnSBdHRH6O+vg5xcZ9g3boN4POpNCHN0f8KQgghxACVlZVizZpIODu74M0353Ltf/vb61r9fHxGIyTkLezfv/cPC9aWMG4O0MZDelKpE7766hvcv38fvXvbQCQSYd++3XB2dsH//Z8Hzp/PQGxsDMrKyuDt7YPVq9fCzMzsifeTdA5UsBJCCCFP6Ouvz7Sqn0AgAAC89tpsvPpqEHc009vbp9XraDoHMC7u00eKwCdTUyPDypXLIRKZYNu2GPD5ghb7GhkZYezY8YiL+wT19fU6z0UEGs9XlclkOrfF5/O5UxgAgM8XwN6+PwCgqOg+EhNP4siRYygvL8e6dWvw7rt/h4eHJyIiluPQoXgsXRr2VPtLOj4qWAkhhJAn9GgR1hoCgYArXgHA2JgPU9O/9lHcUsHYWgqFAqtWrUR5eRkOHDgMS0vxn76mNQWyg4MDKirKUVVVBUvL389jzc/Pg719f+4+r4/buXM7Xn01CDY2tsjIOAehUIRJk6YAAF5+2Q/JyV9TwUo619SshBBCCGmZSqXC2rWrcefObcTExMHGxvZPX6PRaPD9999hwADHPyyWPTy8YGRkhO++S+Paamtrcf78Dxg50lvnay5ezMTt29mYM+ctrq2hoQFqtRoAUFdX38o9I50dHWElhBBCDMS2bR/i/PkMLFsWDoWiHteu/cItc3AYgOrqamzatAETJ06CnV0fyGSNF13dvHkD0dEfa63rlVcC0Lu3DeLiPgUA9OzZEzNmzMTu3bEwNjZG7942OHbsKAAgKEj7vFigsXiOifkYYWERXCHs6uoGjUaN3btjMWzYizh16gReemnis4qDdCBUsBJCCCEGIjPzAgAgLu6TZst2796PgQNfgLm5ORISDqCysgICgQBOTs6IidnVbFpWlUoNtVqj1RYe/jZMTc3w6ad7IJc3Ts0aF7ePm+XqUSdPfoHu3btrXchlZWWFjRujsWtXDL766l8YNcobwcEhbbHrpIPjsac9c5sQQgjpxOrr65Gbmwdr694QCkXtPRxCOgylUoHS0gdwdBzw1Ode0zmshBBCCCFEr1HBSgghhBBC9BoVrIQQQgghRK9RwUoIIYQQQvQaFayEEEIIIUSvUcHagvz8fMyfPx9DhgyBl5cXNm/ejPr6zn0D44KCAqxfvx7Tpk2Ds7Mz/Pz8dPY7d+4cpk+fDjc3N0yYMAGff/65zn4JCQkYN24c3NzcMHPmTFy8ePFZDv+ZSU1NxZIlSzB69GgMGTIE/v7+OHbsGDQa7du5GFouAPDDDz9g9uzZ8PT0hKurK8aPH4/o6Ohm0zMaYjaPksvl8PX1hVQqRVZWltYyQ8smMTERUqm02WPbtm1a/fQzl+dzU52Kigrk5OTg+vXruHkzGwUFBVrLZTIZt/z27dsoKyvXuZ7S0lLcunUb169fR25uLuRy+fMY/jORn5+Pa9eu6XxUVVVx/Qwxm+rqauTm5uHGjRvIzs5GYWEhFApFs37tk03bvWeoYNWhuroac+fOhVwuR2xsLFavXo3Tp0/j73//e3sP7Zm6c+cOzp07B3t7ezg6Oursc+XKFSxZsgTOzs44cOAAZsyYgc2bN+PkyZNa/RISEhATE4M33ngD+/fvh729PUJCQnDr1q3nsStt6tChQxAKhXjnnXewb98+vPTSS4iKisLHH/9+E21DzAUAqqqqMHToUGzatAkJCQmYN28ekpKSEB4ezvUx1GwetWfPHm7mnkcZcjbx8fH48ssvuccbb7zBLdO3XAQCAXg86CwC2trDhw/x228PYGkpRv/+/WFnZws+//epXGtra1FYWAhTU1PY2/eHWNwNv/32GyoqKrTWU1paiuLiYnTvbgV7+/4QCoX49deCDnvgxcbGFgMGDNB6WFpagsfjwdzcHIBhZlNTU4PCwkKIREL069cPNjY2UCgU+PXXX7Xukdte2SgUCvB40JqO+EnRfVh12L9/P/bs2YOzZ8/CysoKAHD69GlERkYiJSWlxWKuo9NoNNxcz++++y6uXbuG5ORkrT4LFixAVVWV1gfHunXr8P333yMjIwNGRkZQKpUYOXIkZs2ahXfeeQcAoFar4e/vD6lUipiYmOe3U22gvLyc+3/QJDo6GsePH8elS5cgFAoNMpeWnDhxAuvWrUNGRgZ69epl8Nnk5ubilVdewerVq/H+++/jn//8J9zc3AAY5vspMTERa9aswYULF5q9r5roYy5FRUWoqKhE165iiEQiALw2XT8AKJVKFBQUws7OFmZmZjr73L9fBI1Gg759+3BtxcUPIZfL4eDgAB4PYIwhLy8flpYWsLZuvGE/Y0BhYQFEIhF69+7d5mNvD/n5v0IkEsLWtnF6WUPMpri4GLW1dXBw6M+11dcrcPduIWxtbbli/vlnw6BQKCCTVaJbNzH3M3oaNNOVDhkZGfDy8tL6ZTpp0iS89957OHfuXKctWJuK1ZYolUpkZmYiMjJSq93f3x8nTpzAjRs34OrqisuXL0Mmk2mdUmBsbIyXX34ZBw8eBGMMPF7b/7J/VnR9qA4aNAgKhQKVlZUQi8UGmUtLxGIxgMZpFw31/8yjoqKiEBQUBAcHB612ykY3fc3FxsYGAFBZWYnHznhpM9XVVWhoqEdtbTVqa6ubLWeMoazsASwsLFBa+oBrV6sVqKkpx4MHxhAIhFAoFJDLK2BmJtDqp9EoUFJSDn4n+ORXKpWQycrA53dDaekDg82muroCDQ0NWvuiUqlQV1eNigoB6upk7ZYNjwd06ybm3jtPq4P9aJ6P3NxczJw5U6tNKGw83J6bm9tOo2p/hYWFaGhowIABA7TaBw4cCKAxN1dXVy6jx/s5OjpCLpejuLi4w32Lfdx//vMfiMVidO/eHfn5+Qafi1qthkqlQk5ODnbv3o2xY8fCzs4OOTk5Bp3NmTNnkJ2djdjYWFy/fl1rmaG/n/z8/FBRUQFbW1vMmjULCxYsgLGxsd7mwuPxYGtri169eqGhoaHN1vuoVatWwdLSEg4ODjh9+jTkcjmcnJywaNEiODo6oqCgAFu2RGHjxo1wdBzMva6yshIRERGIjIzE+PHjcfr0aezZswdJSUn/OxrcKCMjA9HR0Th69Ch69OjxTPbhedm9ezfS0tJw/PhxmJqaGmw2WVlZ2LDhfYSEhGD8+PGoqanB3r178dtvvyEuLg5CobDdshEIBDA2Nm6zfaWCVYfq6mpYWFg0a7ewsNA6udvQNO3749k0PW9aXl1dDaFQ2GwaNktLSwCNb5KO+AHbJCsrC4mJiVi6dCmMjY0pFwBjx45FcXExAMDHxwc7duwAYNj/Z+rq6vDhhx8iIiICXbp0abbcULPp0aMHli9fDnd3d/B4PJw9exY7d+5EcXEx1q9fr/e5GBsbt+mH8KNu376Nhw8folevXoiIiIBAIEBcXBzmz5+Pb7/9FjU1NSgqKkLXrl219tva2hpFRUUoKyuDiYkJSktLUVpaymXRpEuXLigqKoJcLkffvn2fyT48DyqVCqdOnYKXlxe6desGAAabzfDhw7F27Vq8/fbbWL9+PYDGL3cJCQnce6azZEMF61/Q2f709qRayuDRdl19mk6X7sgZlpSUICwsDG5ubggJCdFaZsi57N+/H7W1tcjJycGePXuwaNEiHDp0iFtuiNns3bsX3bt3R2Bg4B/2M7RsfHx84OPjwz339vaGSCTCkSNHsGjRIq7d0HIBGsdeW1uLXbt24YUXXgAAuLi4YPz48fjyyy8xbNgwAIaZzaN+/PFHlJWV6byTjaFlc/nyZaxatQozZ87EuHHjUFNTg3379iEkJATHjx/X+rLc0bOhuwToYGFhgerq5ucPyWQynUdeDUXTt67HjzI3ZdWUjYWFBRQKRbMrapv6Pf7traOQyWQICQmBiYkJ9u7dy131aOi5AICTkxOGDRuGWbNmIS4uDhcvXkRaWprBZnP//n0cPHgQYWFhqKmpQXV1NWprawE0Xq0rl8sNNhtdpkyZArVajZs3bxp0LpaWlrC2tuaKVQDo2bMnBgwYgJycHIPO5lHJyckQi8Xw9vbm2gw1m82bN8PT0xNr166Fl5cXJkyYgAMHDiA/P5+7aLGzZEMFqw6Ojo7NzlVVKpUoLCzstBdctUa/fv0gEAiQl5en1Z6TkwMAXDZN/z6eYW5uLszNzdGrV6/nMNq2pVAosHjxYpSWliI+Pp77MxRg2LnoMmjQIO5cREPN5t69e2hoaMDChQsxfPhwDB8+nDt6+Oabb2LevHkGm82fMeRcWvp8YYzByMjIoLNpUl9fj++++w6TJ0/WulWSoWaTm5sLJycnrTYrKyv07NkThYWFADpPNlSw6uDr64vMzEyt+5OlpaVBqVRi9OjR7Tiy9iUUCuHp6YnU1FSt9uTkZPTo0QPOzs4AgGHDhqFr165ISUnh+qjVaqSmpmL06NHt/meFv0qlUiE8PBzZ2dmIj4+HnZ2d1nJDzaUlV65cgVqtRp8+fQw2m0GDBuHo0aNajzVr1gAAPvjgA7z//vsGm40uKSkpMDY2hrOzs0HnMmbMGJSWluL27dtcW3FxMfLy8iCVSg06myZnz56FXC6Hv7+/VruhZmNra9vsgs6SkhI8fPiQ+6zqNNkw0kxVVRXz8fFhQUFBLCMjg/3rX/9iI0aMYG+//XZ7D+2Zqq2tZampqSw1NZXNnj2bjR49mnteVlbGGGPs8uXLzNnZma1du5ZlZmayPXv2MCcnJ3bixAmtdcXHxzMXFxeWkJDALly4wCIiIpibmxvLzs5uj117KuvWrWMSiYQdOHCAXblyReshk8kYY4aZC2OMLV26lO3du5edPXuW/fTTT+zgwYNs5MiRzN/fnykUCsaY4WbzuMzMTCaRSNgvv/zCtRliNsHBwWz//v0sPT2dpaens3Xr1jGpVMqioqK4PoaYC2OMqVQqNmPGDDZx4kT2zTffsLS0NDZ9+nTm4+PD5HI5Y8xws2myaNEiNmbMGKbRaJotM8Rs/vGPfzCJRMI++OADdv78eZaSksKmTZvGhg8fzoqLi7l+nSEbKlhbkJeXx4KDg5m7uzsbMWIE27RpE6urq2vvYT1Td+/eZRKJROcjMzOT65eens4CAgKYi4sLGz9+PPvss8+arUuj0bADBw6wMWPGMFdXVxYYGMguXLjwPHenzYwdO5ZyacGnn37Kpk2bxoYOHcqGDBnCpk6dynbu3MkV8k0MMZvH6SpYGTO8bDZt2sQmTpzIBg8ezFxdXZmfnx87cuRIswLE0HJpUlpayiIiItiLL77I3N3d2YIFC1hubq5WH0PNprKykrm4uLCPPvqoxT6Glo1Go2FffPEFCwgIYEOGDGEjR45koaGhOgvMjp4NzXRFCCGEEEL0Gp3DSgghhBBC9BoVrIQQQgghRK9RwUoIIYQQQvQaFayEEEIIIUSvUcFKCCGEEEL0GhWshBBCCCFEr1HBSgghhBBC9BoVrIQQQgghRK9RwUoI6ZASExMhlUrh5uaG+/fvN1s+Z84c+Pn5tcPIgIsXL0IqleLMmTPtsv2/6t69e1i4cCE8PDwglUoRFRXV3kPifr737t1r76EQQvQAv70HQAghT0OpVGLnzp34+OOP23soHVZ0dDSuXr2KLVu2wNraGj169GjvIRFCiBY6wkoI6dB8fHyQnJyM7Ozs9h7Kc1dfX4+2mF37zp07GDx4MF566SUMGTIEdnZ2bTA6QghpO1SwEkI6tAULFkAsFv/pEdZ79+5BKpUiMTGx2TKpVIpdu3Zxz3ft2gWpVIrs7GyEhYXhxRdfhIeHB6Kjo6FSqZCXl4f58+dj6NChGDduHA4cOKBzmwqFAtHR0Rg1ahQGDx6M2bNn48aNG836ZWVlYdGiRfDw8ICbmxumT5+OlJQUrT5NfyI/f/481qxZA09PT7i7u0OpVLa4z0VFRYiMjISXlxdcXV0xZcoUHDx4EBqNBsDvpy4UFBQgIyMDUqn0T/8ML5VKsXHjRiQlJWHKlClwd3dHQEAAvv/++2Z9L126hLlz52Lo0KFwd3dHUFAQ0tPTm/X773//i6CgILi5ucHb2xvbt2+HSqXSuf2UlBT87W9/w5AhQzB06FDMnz+/WaZ3797FypUr4e3tDVdXV4wcORJz587FzZs3W9wvQoh+o1MCCCEdmrm5ORYvXoyoqChcuHABXl5ebbbuFStWICAgAEFBQfjxxx8RHx8PlUqFn376Ca+//jrmz5+P06dPY9u2bbC3t8fEiRO1Xh8TEwNnZ2ds3rwZMpkMcXFxmDNnDpKSktC3b18AQGZmJhYsWAB3d3ds2LABXbt2RUpKClauXIn6+noEBgZqrfO9997DmDFj8NFHH6Gurg58vu5f4+Xl5QgKCkJDQwPCw8NhZ2eH9PR0bN26FYWFhdiwYQNcXFzw5ZdfYtmyZejbty9Wr14NAOjZs+cf5pKeno6srCyEhYXBzMwM8fHxWLZsGc6cOcPt188//4zg4GBIJBJERUVBKBTi+PHjWLRoEXbs2IGXX34ZAJCTk4O33noLdnZ2+PDDD2FiYoJjx44hOTm52Xb37duHnTt3IjAwEIsXL0ZDQwMSEhLwxhtv4OTJkxg4cCAAICQkBBqNBqtWrYKtrS0qKipw5coVVFdX/9mPnBCirxghhHRAp06dYhKJhP3yyy9MoVCw8ePHs8DAQKbRaBhjjM2ePZtNnTqV63/37l0mkUjYqVOnmq1LIpGw2NhY7nlsbCyTSCTs4MGDWv2mTZvGJBIJ+/bbb7m2hoYG5unpyZYtW8a1ZWZmMolEwmbMmMGNhzHG7t27x1xcXNjatWu5tsmTJ7Pp06ezhoYGrW2FhoayUaNGMbVarbW/77zzTqvy2bZtG5NIJOzq1ata7e+//z6TSqUsLy+Paxs7dixbuHBhq9YrkUjYyJEjmUwm49pKSkqYk5MT+/TTT7m2WbNmMS8vL1ZTU8O1qVQq5ufnx3x9fblcVqxYwQYPHsxKSkq0+k2ePJlJJBJ29+5dxhhjRUVFzNnZmW3atElrPDU1NWzUqFEsPDycMcZYeXk5k0gk7PDhw63aH0JIx0CnBBBCOjyhUIgVK1bg2rVrSE1NbbP1jhkzRuu5o6MjeDwefH19uTY+nw97e3uddyrw8/MDj8fjntvZ2WHo0KG4ePEiAKCgoAB5eXnw9/cHAKhUKu7h6+uLkpIS5Ofna63z8aO4LcnMzMTAgQMxePBgrfbAwEAwxpCZmdmq9egyYsQIdOnShXtubW2N7t27cxnU1tbi6tWrmDRpEszNzbl+xsbGCAgIwIMHD5CXlweg8bQELy8vWFtba/VrOgLb5Pz581CpVJg2bZpWTiKRCMOHD8fPP/8MABCLxejXrx8SEhJw6NAh3LhxgzsFghDScdEpAYSQTmHq1Kk4ePAgYmJiMGHChDZZp6WlpdZzgUAAU1NTiESiZu01NTXNXv9oEfZoW9MFYqWlpQCArVu3YuvWrTrHUFFRofW8tVfwV1ZW6rx4qunP/ZWVla1ajy5isbhZm1AohEKhAABUV1eDMaZzrI9vv7KyssWcHtWU1SuvvKJzTEZGjcdfeDweDh8+jN27dyM+Ph4ffvghxGIx/P39sWLFCq1CmxDScVDBSgjpFHg8HiIjIzFv3jycOHGi2fKmIvPxi5QeLwjbUlOR9XhbU8HXrVs3AEBoaGiLRbaDg4PW80eP2P4RsViMkpKSZu0PHz7U2vazYGFhASMjo1ZtXywWt5jTo5r6x8bGwtbW9g+3b2dnhy1btgAA8vPzkZqairi4OCiVSmzcuPGv7xAhpN3RKQGEkE5j5MiRGDVqFHbv3g25XK61zNraGiKRCLdu3dJq/+67757ZeJKTk7VuO3X//n1cuXIFHh4eAIABAwagf//+yM7Ohpubm87Hkx4R9PLyQk5ODq5fv67VnpSUBB6PhxEjRjz5jv0JMzMzuLu7Iy0tDfX19Vy7RqPB119/jd69e3OF+IgRI3DhwgWtAlWtVje7S4K3tzf4fD4KCwtbzEoXBwcHLFmyBBKJROcdGgghHQMdYSWEdCqRkZEIDAxEWVkZXnjhBa6dx+MhICAAp06dQr9+/eDk5IRffvlF59XobaW8vBxLly7FrFmzIJPJsGvXLgiFQoSGhnJ9PvjgA4SEhGD+/PmYMWMGevXqhaqqKuTm5uL69euIjY19om2/9dZbSEpKQmhoKMLCwmBra4v09HQcO3YMr732WrMjt20tIiICwcHBePPNNxEcHAyBQIBjx47hzp072LFjB3ekePHixTh79izmzp2LpUuXwsTEBJ9//jnq6uq01tenTx+EhYVh586duHv3Lnx9fWFhYYHS0lJkZWXB1NQUYWFhyM7OxqZNmzB58mTY29tDIBAgMzMTt27dwsKFC5/pPhNCnh0qWAkhnYqzszOmTp2qsxB99913AQDx8fGora3FiBEjsG/fPowbN+6ZjGXlypXIysrCmjVrUFNTg8GDB2PHjh3o168f18fT0xMnT57Evn37sGXLFlRXV0MsFsPR0RFTpkx54m1bWVnhiy++wPbt27F9+3bI5XL06dMHq1atwrx589pi9/6Qh4cHDh8+jF27dmHNmjXQaDRwcnLC3r17MXbsWK6fRCLBoUOHsHXrVqxevRqWlpYICAjApEmTsG7dOq11hoaGwtHREUePHsU333wDpVKJHj16wNXVFa+99hqAxnN8+/Xrh2PHjuHBgwcAwN2ya86cOc98vwkhzwaPsTaYJoUQQgghhJBnhM5hJYQQQggheo0KVkIIIYQQoteoYCWEEEIIIXqNClZCCCGEEKLXqGAlhBBCCCF6jQpWQgghhBCi16hgJYQQQggheo0KVkIIIYQQoteoYCWEEEIIIXqNClZCCCGEEKLXqGAlhBBCCCF67f8DKBgyDUQnG50AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 700x350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Same plot but this time use the best lower bound available for each instance.\n",
    "opt_gaps = [0.001, 0.01, 0.05, 0.1, 0.25]\n",
    "data = []\n",
    "for opt_gap in opt_gaps:\n",
    "    t = results[results[\"opt_tol\"] == 0.001].copy()\n",
    "    t[\"opt_gap\"] = (t[\"objective\"] - t[\"lower_bound\"]) / t[\"lower_bound\"]\n",
    "    t[\"succ\"] = t[\"opt_gap\"] <= opt_gap\n",
    "    t[\"Opt. Tolerance\"] = f\"{100 * opt_gap}%\"\n",
    "    t[\"opt_tol\"] = opt_gap\n",
    "    data.append(t)\n",
    "t = pd.concat(data)\n",
    "t[\"succ_perc\"] = t[\"succ\"] * 100\n",
    "plt.figure(figsize=(7, 3.5))\n",
    "t.rename(columns={\"strategy\": \"Strategy\"}, inplace=True)\n",
    "sns.lineplot(\n",
    "    data=t.sort_values([\"Strategy\", \"opt_tol\"]),\n",
    "    x=\"num_nodes\",\n",
    "    y=\"succ_perc\",\n",
    "    hue=\"Strategy\",\n",
    "    style=\"Opt. Tolerance\",\n",
    "    errorbar=None,\n",
    ")\n",
    "plt.ylabel(\"Instances solved (%)\")\n",
    "plt.xlabel(\"Number of nodes\")\n",
    "plt.xlim(0, 850)\n",
    "plt.title(\"Higher is better\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(PUBLIC_DATA / \"solved_over_size_opt_tol.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A further point to consider is that the optimality gap is always calculated based on the own lower bound.\n",
    "If we need solutions with a quality estimate, this is the way to go.\n",
    "If we do not need the quality estimate, we can also use the best lower bound of all solvers to get a better estimate on the real optimality gap.\n",
    "This is what we do in the next section.\n",
    "The decision on which bound to use depends on the use case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Same plot but this time use the best lower bound available for each instance.\n",
    "opt_gaps = [0.001, 0.01, 0.05, 0.1, 0.2]\n",
    "data = []\n",
    "best_lb = results.groupby([\"instance_name\"])[[\"lower_bound\"]].max().reset_index()\n",
    "for opt_gap in opt_gaps:\n",
    "    t = (\n",
    "        results[results[\"opt_tol\"] == 0.001]\n",
    "        .merge(best_lb, on=\"instance_name\", suffixes=(\"\", \"_best_lb\"))\n",
    "        .copy()\n",
    "    )\n",
    "    t[\"opt_gap\"] = (t[\"objective\"] - t[\"lower_bound_best_lb\"]) / t[\n",
    "        \"lower_bound_best_lb\"\n",
    "    ]\n",
    "    t[\"succ\"] = t[\"opt_gap\"] <= opt_gap\n",
    "    t[\"Opt. Tolerance\"] = f\"{100 * opt_gap}%\"\n",
    "    t[\"opt_tol\"] = opt_gap\n",
    "    data.append(t)\n",
    "t = pd.concat(data)\n",
    "t[\"succ_perc\"] = t[\"succ\"] * 100\n",
    "plt.figure(figsize=(7, 3.5))\n",
    "t.rename(columns={\"strategy\": \"Strategy\"}, inplace=True)\n",
    "sns.lineplot(\n",
    "    data=t.sort_values([\"Strategy\", \"opt_tol\"]),\n",
    "    x=\"num_nodes\",\n",
    "    y=\"succ_perc\",\n",
    "    hue=\"Strategy\",\n",
    "    style=\"Opt. Tolerance\",\n",
    "    errorbar=None,\n",
    ")\n",
    "plt.ylabel(\"Instances solved (%)\")\n",
    "plt.xlabel(\"Number of nodes\")\n",
    "plt.xlim(0, 850)\n",
    "plt.title(\"Higher is better\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(PUBLIC_DATA / \"solved_over_size_opt_tol_best_lb.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparing on unstructured benchmarks\n",
    "\n",
    "The line plots above need a well structured benchmark to compute reliable data points.\n",
    "If you do not have such a benchmark, you may want to go for the following plot which shows how many instances of the benchmark could be solved within a given time limit.\n",
    "This also gives an insight into how fast the model can deal with simple instances.\n",
    "In this specific case, we see that the `CpSatTspSolvingMtz` can solve more instances than `CpSatTspSolvingDantzig`, but `CpSatTspSolvingDantzig` is usually faster for the instances it can solve.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from _conf import TIME_LIMIT, OPTIMALITY_TOLERANCES\n",
    "\n",
    "time_steps = [t_ for t_ in range(0, TIME_LIMIT)]\n",
    "filtered_results = results[results[\"opt_gap\"] <= 1.001 * results[\"opt_tol\"]].copy()\n",
    "\n",
    "\n",
    "def f(strategy, at_time, tol):\n",
    "    t = filtered_results[filtered_results[\"strategy\"] == strategy]\n",
    "    t = t[t[\"runtime\"] <= at_time]\n",
    "    t = t[t[\"opt_tol\"] == tol]\n",
    "    t.drop_duplicates(subset=[\"instance_name\"], inplace=True)\n",
    "    return len(t)\n",
    "\n",
    "\n",
    "data = {\n",
    "    \"Strategy\": [],\n",
    "    \"x\": [],\n",
    "    \"time\": [],\n",
    "    \"Opt. Tolerance\": [],\n",
    "    \"opt_tol\": [],\n",
    "}\n",
    "\n",
    "for strateg in results[\"strategy\"].unique().tolist():\n",
    "    for time in time_steps:\n",
    "        for tol in OPTIMALITY_TOLERANCES:\n",
    "            data[\"Strategy\"].append(strateg)\n",
    "            data[\"x\"].append(time)\n",
    "            data[\"time\"].append(f(strateg, time, tol))\n",
    "            data[\"Opt. Tolerance\"].append(f\"{tol * 100}%\")\n",
    "            data[\"opt_tol\"].append(tol)\n",
    "t = pd.DataFrame(data)\n",
    "plt.figure(figsize=(7, 3.5))\n",
    "sns.lineplot(\n",
    "    data=t.sort_values([\"Strategy\", \"opt_tol\"]),\n",
    "    x=\"x\",\n",
    "    y=\"time\",\n",
    "    hue=\"Strategy\",\n",
    "    style=\"Opt. Tolerance\",\n",
    "    errorbar=None,\n",
    ")\n",
    "plt.ylabel(\"Num. instances solved\")\n",
    "plt.xlim(-5, 150)\n",
    "plt.xlabel(\"Time (s)\")\n",
    "plt.title(\"Higher is better\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(PUBLIC_DATA / \"cactus_plot_opt_tol.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from _conf import TIME_LIMIT, OPTIMALITY_TOLERANCES\n",
    "\n",
    "time_steps = [t_ for t_ in range(0, TIME_LIMIT)]\n",
    "filtered_results = results[results[\"opt_gap\"] <= 1.001 * results[\"opt_tol\"]].copy()\n",
    "\n",
    "\n",
    "def f(strategy, at_time, tol):\n",
    "    t = filtered_results[filtered_results[\"strategy\"] == strategy]\n",
    "    t = t[t[\"runtime\"] <= at_time]\n",
    "    t = t[t[\"opt_tol\"] == tol]\n",
    "    t.drop_duplicates(subset=[\"instance_name\"], inplace=True)\n",
    "    return len(t)\n",
    "\n",
    "\n",
    "data = {\n",
    "    \"Strategy\": [],\n",
    "    \"x\": [],\n",
    "    \"time\": [],\n",
    "    \"Opt. Tolerance\": [],\n",
    "}\n",
    "\n",
    "for strateg in results[\"strategy\"].unique().tolist():\n",
    "    for time in time_steps:\n",
    "        for tol in OPTIMALITY_TOLERANCES[:1]:\n",
    "            data[\"Strategy\"].append(strateg)\n",
    "            data[\"x\"].append(time)\n",
    "            data[\"time\"].append(f(strateg, time, tol))\n",
    "            data[\"Opt. Tolerance\"].append(tol * 100)\n",
    "t = pd.DataFrame(data)\n",
    "plt.figure(figsize=(7, 3.5))\n",
    "sns.lineplot(\n",
    "    data=t.sort_values(\"Strategy\"), x=\"x\", y=\"time\", hue=\"Strategy\", errorbar=None\n",
    ")\n",
    "plt.ylabel(\"Num. instances solved to optimality\")\n",
    "plt.xlim(-5, 150)\n",
    "plt.xlabel(\"Time (s)\")\n",
    "plt.title(\"Higher is better\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(PUBLIC_DATA / \"cactus_plot.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instance_name</th>\n",
       "      <th>num_nodes</th>\n",
       "      <th>time_limit</th>\n",
       "      <th>strategy</th>\n",
       "      <th>opt_tol</th>\n",
       "      <th>runtime</th>\n",
       "      <th>objective</th>\n",
       "      <th>lower_bound</th>\n",
       "      <th>opt_gap</th>\n",
       "      <th>opt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>random_euclidean_100_3</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>Iterative Dantzig</td>\n",
       "      <td>0.100</td>\n",
       "      <td>90.111767</td>\n",
       "      <td>7.416302e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>random_euclidean_100_3</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>Iterative Dantzig</td>\n",
       "      <td>0.250</td>\n",
       "      <td>90.242522</td>\n",
       "      <td>7.416302e+07</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>random_euclidean_100_3</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.001</td>\n",
       "      <td>90.424638</td>\n",
       "      <td>7.564729e+07</td>\n",
       "      <td>72159364.0</td>\n",
       "      <td>0.046108</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>random_euclidean_100_3</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.010</td>\n",
       "      <td>90.387232</td>\n",
       "      <td>7.416302e+07</td>\n",
       "      <td>71652903.0</td>\n",
       "      <td>0.033846</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>random_euclidean_100_3</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.050</td>\n",
       "      <td>90.371634</td>\n",
       "      <td>7.742063e+07</td>\n",
       "      <td>72885906.0</td>\n",
       "      <td>0.058573</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2335</th>\n",
       "      <td>random_euclidean_400_9</td>\n",
       "      <td>400</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.010</td>\n",
       "      <td>157.327746</td>\n",
       "      <td>2.092240e+09</td>\n",
       "      <td>63258296.0</td>\n",
       "      <td>0.969765</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2336</th>\n",
       "      <td>random_euclidean_400_9</td>\n",
       "      <td>400</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.050</td>\n",
       "      <td>150.462334</td>\n",
       "      <td>2.071005e+09</td>\n",
       "      <td>63444508.0</td>\n",
       "      <td>0.969365</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2337</th>\n",
       "      <td>random_euclidean_400_9</td>\n",
       "      <td>400</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.100</td>\n",
       "      <td>161.027150</td>\n",
       "      <td>2.578843e+09</td>\n",
       "      <td>63785063.0</td>\n",
       "      <td>0.975266</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2338</th>\n",
       "      <td>random_euclidean_400_9</td>\n",
       "      <td>400</td>\n",
       "      <td>90</td>\n",
       "      <td>Miller-Tucker-Zemlin</td>\n",
       "      <td>0.250</td>\n",
       "      <td>155.932914</td>\n",
       "      <td>1.974268e+09</td>\n",
       "      <td>63062886.0</td>\n",
       "      <td>0.968058</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2377</th>\n",
       "      <td>random_euclidean_50_8</td>\n",
       "      <td>50</td>\n",
       "      <td>90</td>\n",
       "      <td>Iterative Dantzig</td>\n",
       "      <td>0.001</td>\n",
       "      <td>89.984819</td>\n",
       "      <td>7.523738e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1025 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               instance_name  num_nodes  time_limit              strategy  \\\n",
       "0     random_euclidean_100_3        100          90     Iterative Dantzig   \n",
       "1     random_euclidean_100_3        100          90     Iterative Dantzig   \n",
       "2     random_euclidean_100_3        100          90  Miller-Tucker-Zemlin   \n",
       "3     random_euclidean_100_3        100          90  Miller-Tucker-Zemlin   \n",
       "4     random_euclidean_100_3        100          90  Miller-Tucker-Zemlin   \n",
       "...                      ...        ...         ...                   ...   \n",
       "2335  random_euclidean_400_9        400          90  Miller-Tucker-Zemlin   \n",
       "2336  random_euclidean_400_9        400          90  Miller-Tucker-Zemlin   \n",
       "2337  random_euclidean_400_9        400          90  Miller-Tucker-Zemlin   \n",
       "2338  random_euclidean_400_9        400          90  Miller-Tucker-Zemlin   \n",
       "2377   random_euclidean_50_8         50          90     Iterative Dantzig   \n",
       "\n",
       "      opt_tol     runtime     objective  lower_bound   opt_gap    opt  \n",
       "0       0.100   90.111767  7.416302e+07          0.0  1.000000  False  \n",
       "1       0.250   90.242522  7.416302e+07         18.0  1.000000  False  \n",
       "2       0.001   90.424638  7.564729e+07   72159364.0  0.046108  False  \n",
       "3       0.010   90.387232  7.416302e+07   71652903.0  0.033846  False  \n",
       "4       0.050   90.371634  7.742063e+07   72885906.0  0.058573  False  \n",
       "...       ...         ...           ...          ...       ...    ...  \n",
       "2335    0.010  157.327746  2.092240e+09   63258296.0  0.969765  False  \n",
       "2336    0.050  150.462334  2.071005e+09   63444508.0  0.969365  False  \n",
       "2337    0.100  161.027150  2.578843e+09   63785063.0  0.975266  False  \n",
       "2338    0.250  155.932914  1.974268e+09   63062886.0  0.968058  False  \n",
       "2377    0.001   89.984819  7.523738e+07          0.0  1.000000  False  \n",
       "\n",
       "[1025 rows x 10 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results[results[\"opt_gap\"] >= results[\"opt_tol\"]]"
   ]
  },
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   "metadata": {},
   "source": []
  }
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